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Asthma burden in the US is not evenly distributed. Although asthma prevalence varies widely across urban neighborhoods, little attention has been paid to the community as a key contributor.
To determine the effect of positive socio-environmental community factors on childhood asthma prevalence in Chicago.
From 2003–2005, an asthma screening survey was conducted among children attending Chicago Public/Catholic K-8 schools. One hundred five schools participated, yielding a stratified representation of 4 race-income groups. Positive community factors, such as social capital, economic potential and community amenities, were assessed using the Metro Chicago Information Center’s Community Vitality Index.
Of the surveys returned, 45,177 (92%) were geocoded into 287 neighborhoods. Neighborhoods were divided into quartile groups by asthma prevalence (mean: 8%, 12%, 17%, 25%). Community vitality (54% vs. 44%, p<0.0001) and economic potential (64% vs. 38%, p<0.0001) were significantly higher in neighborhoods with low asthma prevalence. Neighborhood interaction (36% vs. 73%, p<0.0001) and stability (40% vs. 53%, p<0.0001) were significantly higher in neighborhoods with high asthma prevalence.
Overall, positive factors explained 21% of asthma variation. Childhood asthma increased as the Black population increased in a community (p<0.0001). Accordingly, race/ethnicity was controlled. In Black neighborhoods, these factors remained significantly higher in neighborhoods with low asthma prevalence. When considered alongside socio-demographic/individual characteristics, overall community vitality as well as social capital continued to contribute significantly to asthma variation.
Asthma prevalence in Chicago is strongly associated with socio-environmental factors thought to enrich a community. A deeper understanding of this impact may lend insight into interventions to reduce childhood asthma.
Asthma is the leading chronic illness of childhood, affecting over 9 million children; however, the burden is not equally distributed in the United States.1 Racial differences in prevalence have been identified as an important public health concern,2 as has the problem of increased asthma prevalence in certain U.S. urban populations.3–5
Chicago, a city with one of the highest asthma rates in the country, has asthma mortality twice the national average.6–8 Chicago hospitalization rates have also been shown to be twice as high as suburban Chicago and overall US rates.8 However, research demonstrates that childhood asthma rates in Chicago vary widely based on the neighborhood in which a child lives.9
Researchers exploring the causes of the asthma burden in Chicago and other high risk urban areas have demonstrated that mortality rates are associated with individual factors such as race and community social economic status.5, 10 Some negative community-level physical environment factors, such as neighborhood violence, air pollution, and housing conditions, have also been implicated in affecting childhood asthma prevalence and morbidity.11–15 To our knowledge, the effect of social and environmental factors thought to enrich a community, i.e. positive community factors, has not been fully characterized. In a study limited to a comparison of 3268 adults in Chicago, it was suggested that collective efficacy, a measure of residents’ trust, attachment, and capacity for mutually beneficial action, was protective against asthma and breathing problems.16
The Chicago Initiative to Raise Asthma Health Equity (CHIRAH) Study was designed to better characterize the factors associated with asthma burden. Initial findings have suggested a wide variation in childhood asthma prevalence.9 Therefore, the purpose of this study is to determine the effect of positive community factors such as social capital, economic potential and community amenities on childhood asthma prevalence in Chicago neighborhoods.
This report is based on a cross-sectional survey screening for asthma that was conducted as part of the Chicago Initiative to Raise Asthma Health Equity (CHIRAH) study. This study consisted of a large sample of children attending Chicago public and Catholic elementary and middle schools during the 2003–2004 and 2004–2005 school years. An overview of the study methods follow; for further details on study methods refer to Shalowitz et al., 2007.17
In 2004, Chicago Public Schools (CPS) had 320,557 students in 486 elementary schools. CPS students were 50% African-American, 38% Hispanic, and 9% White. Eighty-five percent of CPS students were considered low-income, defined as coming from families who are receiving public aid, living in institutions for neglected or delinquent children, being supported in foster homes with public funds, or being eligible to receive free or reduced-price lunches. In 2004, the Archdiocese of Chicago had 37,333 students in 126 elementary schools. Archdiocese students were 14% African-American, 17% Hispanic and 62% White. Twenty-four percent of Archdiocese students were low-income (includes Chicago and suburbs; Chicago-only estimates are higher).
To gain a representative sample of students, schools were stratified first by race and then income. Schools were identified by population proportionate and cluster sampling methods within each of the 4 race-income sampling groups (high Black/mid-income; high Black/low-ncome; low Black/mid-income; low Black/low-income), resulting in a final sample of 105 schools. For each school, all children in grades K-8 were eligible to be surveyed and asked to participate. A total of 48,917 (79%) completed surveys were returned. For further details on school sample, refer to the Online Repository.
The screening survey was distributed at the schools and taken home by the students for an adult caregiver to complete in English or Spanish. It consisted of questions including the child’s birth date, height, weight, gender, report of physician or nurse diagnosed asthma, age at diagnosis, the race/ethnicity of the child, current asthma status, relationship to the child of the person completing the survey, the names and ages of others living in the same household with asthma, the child’s home address, and a short asthma symptom screening tool—the Brief Pediatric Asthma Screen Plus.18, 19 Our analyses included only children with physician or nurse diagnosed asthma as reported by an adult caregiver. The sampled subjects were geocoded using ArcGIS US Streetmap and linked with neighborhoods (ESRI GIS and Mapping Software; Redlands, CA).
In order to study the possible community-level factors, all children were assigned to a neighborhood. The Chicago neighborhoods used in this analysis represent neighborhoods as defined by the Project on Human Development in Chicago Neighborhoods (PHDCN).20 The PHDCN Scientific Directors defined neighborhoods spatially, i.e. as a collection of people and institutions occupying a contiguous subsection of a larger community. The project collapsed 847 census tracts in the city of Chicago to form 343 neighborhoods. The predominant guideline in formation of the neighborhoods was that they should be as ecologically meaningful as possible, composed of geographically contiguous census tracts, and internally homogenous on key census indicators. The project settled on an ecological unit of about 8,000 people, which is smaller than the 77 established community areas in Chicago (of which the average size is almost 40,000 people), but large enough to approximate local communities. Geographic boundaries (e.g., railroad tracks, parks and freeways) and knowledge of Chicago's community areas guided this process. Our sample consisted of children from 287 of the 342 PHDCN neighborhoods; 56 neighborhoods had fewer than 15 children from our sample and were not included in the study.
Community-level socio-environmental characteristics were assigned to each neighborhood and were part of the Community Vitality Index (CVI). The census-tract level CVI was developed by and obtained from the Metro Chicago Information Center (MCIC), an official Census Information Center. The MCIC CVI provides a composite score, comprised of 3 components: Social Capital (33.3%), Economic Potential (33.3%) and Community Amenities (33.3%). Each of these components consists of four sub-indices (Table eI). Sub-index scores range from 1 (lowest observed value) to 100 (highest observed value). The values are averaged and then ranked together to produce the overall CVI and CVI component scores for each census tract.
The MCIC CVI generates a score from 1–100 for every census tract in the six-county Chicago metropolitan region. The score is a way to "grade" each census tract in relation to the region as a whole. For example, if a tract has a CVI score of 87, it means that 87% of the tracts in the region have lower CVI scores. Indicators in this index model were determined through a review of the literature and current practices, small area data availability, and stakeholder input. All data indicators are normalized to account for population density differences. A neighborhood’s community indices are the averages of its corresponding census-tract level indices. (For detailed CVI methodology, see http://info.mcfol.org/www/datainfo/cvi/tech_methodology.asp.)
Neighborhoods were assigned to a quartile group according to childhood asthma prevalence. The multiple t-test was performed to evaluate the Community Vitality Index across each quartile group. This method allowed us to test the null hypothesis of no difference in the mean between three or more groups simultaneously and produces an accurate assessment of the effects of community factors on asthma prevalence.21,22 Proc Multtest (Bonferroni option) in SAS was used for this analysis (SAS Institute, Inc; Cary, NC).
In order to accommodate the significant effects of neighborhood racial/ethnic composition on asthma prevalence, we grouped neighborhoods with greater than two-thirds of a specific race, namely White, African-American and Hispanic. We then applied multiple group analysis to further evaluate the effects of community factors on asthma prevalence specific to neighborhoods categorized by race. Mplus3.0 was used to implement the multiple group analysis (Muthén & Muthén; Los Angeles, CA).
Multilevel logistic regression analysis was performed for 45,309 individuals nested within 287 neighborhoods to estimate the effect of the twelve CVI sub-indices on childhood asthma neighborhood variance. A similar analysis was conducted looking at individual and neighborhood factors alongside CVI to assess the impact of each sub-index and sub-index item on childhood asthma neighborhood variance. SAS GLIMMIX was used for multilevel analysis (SAS Institute, Inc; Cary, NC). For further details on the multilevel logistic regression analysis, refer to the Online Repository.
The institutional review boards of Northwestern University and the Cook County Bureau of Health Services approved the school screening protocol. The Chicago Public School board and the Archdiocese of Chicago approved the asthma screening protocol in their respective schools.
A total of 48,917 children were screened and 45,177 (92%) were successfully geocoded and resided in one of the 287 Chicago neighborhoods. Among these children, 11% were ages 3–5 years old, 34% were ages 6–8 years, 33% were 9–11 years and 22% were 12 years and older. Forty-nine percent were male and 29% self-identified as White, 29% as Black and 43% as Hispanic. The asthma prevalence of the overall study population was 13%. White and Hispanic children had a mean asthma prevalence of 10% and 11%, respectively, whereas Black children had a mean asthma prevalence of 20% (p<0.0001). Nine percent of children in the sample had a household member with asthma. (Table I)
To assess the effect of positive community factors on asthma prevalence, we categorized the 287 neighborhoods into quartile groups (Figure 1). Each neighborhood quartile group was characterized by its mean asthma prevalence: 8% in Group 1, 12% in Group 2, 17% in Group 3, and 25% in Group 4 (Table II). As seen is Table II, the mean Community Vitality Index score differed significantly across each neighborhood quartile group; as asthma prevalence decreased, the mean CVI percentile scores improved significantly (p<0.001).
There were notable differences seen in the scores for each CVI component and the corresponding sub-indices. The overall social capital of a neighborhood did not reach statistical significance because the sub-indices measuring social capital were significant in opposite directions. Neighborhoods with more civic engagement (p<0.0001) and community diversity (p<0.0001) had lower childhood asthma rates. In contrast, neighborhoods with more interaction potential (p<0.0001) and stability (p<0.05) had higher asthma prevalence. (Table II)
Neighborhoods with evidence of economic vigor had lower asthma prevalence rates (p<0.0001), ranging from 64% in the low prevalence neighborhoods to 38% in the high prevalence neighborhoods. Lower asthma rates were also seen in neighborhoods with greater commercial vitality (p<0.0001), buying power (p<0.0001), and workforce potential (p<0.0001). Asthma prevalence was not associated with evidence of confidence and investment in a community. (Table II)
Neighborhoods with more community amenities also had lower childhood asthma prevalence (p<0.05). Lower asthma rates were particularly common in neighborhoods with many cultural/entertainment facilities and restaurants (p<0.0001). However, there were more community institutions (e.g. libraries, universities, etc.) in neighborhoods with high asthma prevalence (p<0.05). Health and human service facilities seemed to be distributed equally among all neighborhoods, and were not significantly associated with asthma prevalence. (Table II)
As the African American population increased in a community, so did the childhood asthma prevalence (p<0.0001). To investigate whether CVI indicators were still predictive of asthma prevalence when race/ethnicity was controlled, neighborhoods with ≥67% of their population classified as White or Black were analyzed individually. Since only 32 neighborhoods had greater than two-thirds Hispanic population, analyses were not done on this group.
One hundred eight neighborhoods had greater than two thirds of their population reported as African American. As asthma prevalence increased in these primarily African American neighborhoods, the overall CVI score significantly decreased (p<0.05). None of the 3 CVI component scores reached statistical significance. However, commercial vitality, an indicator of economic potential, was statistically significant (p<0.05), with higher commercial vitality predictive of lower asthma prevalence.
The predominant population in 72 Chicago neighborhoods was White. In these neighborhoods, neither the total CVI score nor any of the component scores were significantly related to asthma prevalence. However, community diversity, an indicator of social capital, was nearly significant (p<0.1), with greater diversity corresponding to higher asthma rates. Economic potential was nearly significant (p<0.1), with more potential for community development associated with lower asthma prevalence.
Eleven of the 12 CVI sub-indices, with the exception of the degree of confidence and investment in a community, were significantly associated with the neighborhood asthma variation (Table III). That being said, each sub-index had a small individual impact on the variation seen. Together, indicators of social capital explained 43% of the neighborhood variation seen [from values for neighborhood variance: (Model I – Model VI)/Model I, from Table III]. Indicators of economic potential explained 29% of the variation while indicators of community amenities explained 50%.
In Table IV, individual characteristics as well as community race and SES were added into the models. A child’s age, gender, household asthma history, and community racial composition were all significant factors associated with the variation in neighborhood asthma prevalence. A community’s SES, however, was not significantly associated when modeled with CVI/CVI components and individual characteristics of the child. The Community Vitality Index continued to contribute significantly when community race was added to the model. The social capital component played a significant role in explaining a degree of the variation seen in asthma prevalence by neighborhood in spite of the inclusion of a community’s racial/ethnic composition. Absent race, overall CVI accounted for 50% of the variation in neighborhood asthma; with the inclusion of race, CVI continued to explain 21% of the variance [from values for neighborhood variance: (Model III – Model IV)/Model I, from Table IV].
To our knowledge, our study is the first to show the influence of positive community factors on childhood asthma prevalence. The overall Community Vitality Index was significantly associated with asthma prevalence, with higher CVI scores in neighborhoods with low asthma rates. Specifically, communities with low childhood asthma rates had greater potential for economic development and, from a social perspective, were more diverse and civically engaged. They also had more restaurants and cultural/entertainment facilities. Neighborhoods with high childhood asthma had more community institutions, such as libraries and universities, and more potential for community interaction; these communities also tended to be more stable. Health and human service agencies, including medical care facilities, were not significantly associated with asthma prevalence. Positive community factors had an influence on neighborhood asthma variation. After controlling for individual factors, community race, and SES, a community’s social capital continued to contribute significantly. The overall Community Vitality Index remained significant but contributed less to neighborhood asthma variation after the addition of community race. Accordingly, race may serve as a proxy for many socio-cultural and environmental risk factors for asthma in our study.
Under the social capital component, neighborhoods with more civic engagement (higher percentage of registered voters) and increased diversity (ethnicity, income and age) were associated with low asthma prevalence. Interestingly, neighborhoods with high asthma had double the potential for community interaction. Previous studies have shown that psychosocial factors, including lack of social support networks, lead to increased asthma hospitalizations.23, 24 However, this apparent conflict may be explained by the measure with which interaction was measured. In this study, interaction was measured by the percent of households not linguistically isolated or comprised of a single person living alone and having at least one household member not in the labor force. While one can understand how these factors may lead to increased interaction, they may also signify crowding and poverty, which are consistent with increased indoor pollutants and asthma rates.25, 26 Future researchers may wish to question participants about personal social support and interaction networks to measure this variable accurately.
Neighborhoods with high asthma rates were also more stable, indicating that residents in the community were less likely to move. Prior studies have linked more residential stability both with higher27 and lower28 asthma rates based on cockroach allergen levels in the home. In the former study, higher asthma rates in more stable communities were attributed to less thorough and frequent maintenance cleaning in homes occupied for a longer period of time.27 In the latter study, lower asthma rates in more stable communities were suggested to indicate a better built environment in these homes.28
If the measures used herein truly capture social support and stability, these positive associations are encouraging for the development of effective asthma interventions, known to require an interactive and stable community in which individuals can develop shared commitments to desired outcomes.29
Poverty has been shown to be associated with asthma prevalence, hospitalizations and mortality in multiple studies.26, 30, 31 Likewise, we found a neighborhood’s economic potential to be strongly associated with asthma prevalence. Specifically, the greater the number of businesses, number of business loans, aggregate income, degree of educational attainment, number of wage earners and employment rate were all associated with lower asthma rates. In predominantly Black neighborhoods, although the overall potential for economic growth was not associated with asthma prevalence, there were significantly more businesses in neighborhoods with lower asthma rates.
Surprisingly, the number of mortgages, home improvement loans and occupied dwelling units—all representative of the degree of confidence and investment in a community—was not significantly different among neighborhoods. This may be because areas with higher asthma prevalence may also have a higher density of people, resulting in an illusory inflation in the number of mortgages and home improvement loans. Another possible explanation may be the unusually high real estate activity in Chicago in early 2000; many buildings in low income neighborhoods were sold and rehabbed for section 8 rentals, which may have disproportionately increased the number of occupied properties in neighborhoods with high asthma prevalence.
The association of community amenities and asthma rates may be explained by basic supply and demand analysis. Neighborhoods with low asthma rates had more restaurants and cultural/entertainment facilities because they had higher aggregate community income and, accordingly, were able to invest more in these facilities. Neighborhoods with high asthma had more libraries, houses of worship and institutions of higher education. This too is understandable, as these facilities are typically not for profit and are often managed by the local government and religious organizations. Interestingly, the number of health and human services agencies was not related to asthma prevalence. However, previous studies have shown that poor children are less likely to utilize appropriate health services.32–34 Although it seems health centers exist equally in neighborhoods regardless of asthma prevalence, a child in a community with high asthma rates may have difficulty accessing services due to insurance, knowledge, and other individual factors.
There are, as with all studies, limitations to the design that need to be highlighted. We obtained community data from the 2000 census and individual data was collected from 2003–2005. As the community data is three to five years older than the individual data, there may be some discrepancy. Further, our study was based on school samples of children and a certain census per school. For this reason we did not have an exact census of children from each neighborhood and any neighborhood with less then 15 children was not included. Also, a small bias may exist for children not yet in school. Our sample of children, however, was large and 84% of Chicago neighborhoods were represented. Finally, we recognize that use of the Community Vitality Index is relatively new to the field of medical research (we are aware of one study in progress using this measure), and, as such, the reliability of its measurement in the face of a counterintuitive finding is a potential limitation and open for further investigation. Our primary objective is to initiate an investigation into the impact of positive social and environmental community characteristics on childhood asthma prevalence. We encourage researchers to take note of these potentially mutable factors and further our work, through their own investigation, using a host of measures to validate (or challenge) our findings.
Prior studies clearly identify the causes of pediatric asthma to be multifactorial. Negative community factors that have been associated with asthma prevalence include: exposure to air pollution,4, 35, 36 housing problems including sensitization to cockroach,37–39 dust mite,38, 40 mouse41, 42 and rat allergens,43 decreased exposure to endotoxins (the hygiene hypothesis),44–46 community income and education,26, 47 and exposure to violence.15, 48 Individual factors known to be associated with asthma include age, gender,49, 50 race,30, 51 family history,52 smoking,53, 54 diet55, 56 and stress.57, 58 Because asthma is such a complex disease, several of these factors may be related to the positive factors discussed. For example, in neighborhoods with more economic potential, there may be less indoor and outdoor pollutants and less indoor allergen exposure due to a better built environment.
Regardless, with childhood asthma prevalence at a historic high and disparities increasing among low-income and minority population,59 further insight is clearly needed to combat this growing problem. Positive community factors have rarely been examined as potential protective factors in childhood asthma even though asthma prevalence has been shown to vary widely by neighborhood.9 Our results suggest that positive community factors are associated with childhood asthma prevalence and further investigation is warranted. A deeper understanding of positive community factors and the interplay of these factors with individual and negative community factors is an essential step to determining the true causes of neighborhood variation in childhood asthma rates.
We would like to thank the CHIRAH team, the Chicago Public Schools and the schools of the Archdiocese of Chicago, Christine Janowiak and Elizabeth Springston, without whom this project would not have been possible. We would also like to thank our funders: Chicago Initiative to Raise Asthma Health Equity (CHIRAH) is funded by the National Heart Lung and Blood Institute (NHLBI), 5U01 HL072478-05 and Dr. Ruchi Gupta is funded by the NICHD through a Child Health Research Career Development Award, "Faculty Development Program for Pediatric Clinician-scientists," K12 HD052902. Dr. Gupta had full access to all of the data in the CHIRAH study and takes responsibility for the integrity of the data and the accuracy of the analysis.
Our financial sponsors played no role in the development of this manuscript absent their monetary contributions. The authors have no conflict of interest, either real or perceived, in the publication and dissemination of this manuscript.
Grant Support: NHLBI 5U01 HL072478-05; NICHD K12 HD052902
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Clinical Implications: An understanding of the social and environmental community factors that may be protective against childhood asthma will lend insight into the allocation of public health resources.
Capsule Summary: Asthma prevalence in Chicago neighborhoods is strongly associated with social and environmental factors thought to enrich a community. A deeper understanding of this impact may aid in the development of interventions to decrease childhood asthma.