The influence of caregiver’s psychosocial status on childhood asthma and obesity

The influence of caregiver’s psychosocial statuson childhood asthma and obesityLisa K. Sharp, PhD*; Laura M. Curtis, MS†; Giselle Mosnaim, MD, MS‡;Madeleine U. Shalowitz, MD§; Cathy Catrambone, PhD�; and Laura S. Sadowski, MD, MPH¶

Background: The prevalence of childhood asthma and childhood overweight has increased in the last 2 decades, dispropor-tionately burdening ethnic minority children and those living in poverty with no clear understanding of underlying mechanisms.

Objective: To explore the influence of demographic variables, childhood obesity (adjusted body mass index �95thpercentile), caregivers’ smoking status, and caregiver psychosocial status on asthma severity and asthma control in an urbansample of children with persistent asthma.

Methods: Child (with asthma)–caregiver dyads were recruited from public and archdiocese schools in Chicago, Illinois, aspart of the Chicago Initiative to Raise Asthma Health Equity. Data were collected as part of the baseline face-to-face surveysconducted within the community.

Results: The 531 dyads were divided into 2 groups: 294 taking controller medications were in the asthma control analyses and237 taking rescue medications only were in the asthma severity analyses. In multivariate models, asthma control was significantlyworse in obese children (odds ratio [OR], 1.89; 95% confidence interval [CI], 1.17–3.05), African American children (OR, 2.16;95% CI, 1.05–4.46), and those with caregivers who had higher stress (OR, 1.09; 95% CI, 1.01–1.18). Older children had bettercontrol (OR, 0.79; 95% CI, 0.69–0.90). Children with caregivers who wanted more asthma-specific social support were morelikely to have moderate to severe asthma (OR, 2.07; 95% CI, 1.06–4.05).

Conclusion: In this community-based sample of children with active asthma, asthma control and asthma severity wereassociated with different factors. Caregiver variables were significant in both outcomes, and childhood obesity was associatedonly with poor asthma control.

Ann Allergy Asthma Immunol. 2009;103:386–394.

INTRODUCTIONChildhood asthma is a complex public health problem thataffects approximately 9 million children in the United States.1

Rates doubled between 1980 and 1995, with recent estimatesshowing a stabilization in new asthma cases.2 Childhoodoverweight (defined by a body mass index [BMI] �85thpercentile adjusted for age and sex) represents another prev-alent public health concern, which has tripled between 1980and 2000. Estimates from the 2003 to 2006 National Healthand Nutrition Examination Survey indicate that 31.9% ofchildren were overweight and 16.3% were obese (defined bya BMI �95th percentile adjusted for age and sex).3

Increasingly, researchers have noted the co-occurrence ofchildhood obesity and asthma,4–7 which both disproportion-ately affect racial/ethnic minorities and the economicallydisadvantaged.1,8 The mechanisms linking asthma and over-weight are unclear4,7,9–11; nonetheless, their co-occurrence isconcerning because mounting evidence suggests that childrenwith increased BMI experience higher asthma morbidity.12

Relative to normal-weight children with asthma, overweightchildren with asthma experience increased medication use,wheezing, emergency department use, missed school days,longer hospital stays, lower pulmonary function, and worsequality of life.12–17 Although these studies consider demo-graphic variables that might influence asthma morbidity,many do not consider the psychosocial status of the child’scaregiver. This omission may be important because anemerging literature suggests that asthma and obesity are bothinfluenced by caregiver depression and stress.18–22 To ourknowledge, this is the first study to explore the relationshipbetween both childhood obesity and caregiver’s psychosocialstatus on asthma morbidity. The study is further distinguishedby the selection of asthma outcomes. Much of the childhoodasthma research relies on individual asthma-related out-comes, such as symptoms or health care use.13,16 This studyuses 2 summary variables, asthma control and asthma sever-ity, as defined by the National Asthma Education PreventionProgram Expert Panel Report 3 (NAEPP/EPR-3).23 Per thereport, severity is defined as the intrinsic intensity of the

Affiliations: * Department of Medicine, Section of Health PromotionResearch, University of Illinois at Chicago, Chicago, Illinois; † Institute forHealthcare Studies, Northwestern University Feinberg School of Medicine,Chicago, Illinois; ‡ Department of Immunology/Microbiology, Rush Medi-cal College, Chicago, Illinois; § Department of Pediatrics, Section for Child& Family Health Studies, NorthShore University HealthSystem, Chicago,Illinois; � Rush University College of Nursing, Chicago, Illinois; ¶ Depart-ment of Medicine, Stroger Hospital of Cook County, Chicago, Illinois.

Disclosures: Authors have nothing to disclose.Funding Sources: CHIRAH was funded by National Heart, Lung, and

Blood Institute grant 5U01 HL072478-05.Disclaimer: The contents of this article are solely the responsibility of the

authors and do not necessarily represent the official views of the NationalInstitutes of Health.

Received for publication March 20, 2009; Received in revised form June12, 2009; Accepted for publication June 15, 2009.

386 ANNALS OF ALLERGY, ASTHMA & IMMUNOLOGY

disease process and is most easily and directly measured in apatient who is not receiving long-term control therapy. Con-trol is defined as the degree to which the manifestations ofasthma are minimized by therapeutic intervention and thegoals of therapy are met.21

METHODS

Overview of Sample RecruitmentThe sample was recruited through the Chicago Initiative toRaise Asthma Health Equity (CHIRAH) project, which rep-resents 1 of the National Heart, Lung, and Blood InstituteCenters of Excellence in Reducing Asthma Disparities.CHIRAH provides a unique opportunity to report on theburden of asthma in a large urban environment known to have1 of the highest asthma mortality rates in the United States.24

The cohort was established between 2003 and 2005.Screening of 62,005 elementary school children in the Chi-cago, Illinois, public and archdiocese schools led to 48,917returned surveys. Of those, 561 child-caregiver dyads wereeligible because they had a child between 8 and 14 years ofage with physician- or nurse-diagnosed asthma, they residedin Chicago, the caregivers were fluent in English, and theyhad a child who required the use of any asthma medication(ie, rescue or controller) for at least 8 weeks of the prior 12months. This report focuses on the 531 child-caregiver dyadswith complete data on the variables of interest. For furtherdetails on study methods, refer to Weiss et al.25

Caregivers provided written informed consent and childrenprovided written informed assent before completing in-per-son baseline interviews in community settings. The researchprotocol was approved by the institutional review boards ofall participating research institutions and the Chicago publicand archdiocese schools.

Demographic VariablesDemographic information included caregiver’s report of thechild’s sex, age, insurance status, and race/ethnicity alongwith his/her own sex, age, highest educational level attained(less than high school diploma, high school or general edu-cational development graduate, college graduate), andgrouped classification of household income level (�$15,000,$15,000-$30,000, $30,000-$50,000, and �$50,000).

Child VariablesAsthma symptoms. Asthma symptoms were measured by2-week caregiver recall of the child’s daytime symptoms(wheezing, chest tightness, cough, and shortness of breath)and separately for nighttime awakening from symptoms. Thisprovided 2 variables, each ranging from 0 to 14.

Acute asthma exacerbations. Exacerbations were consid-ered to be the total number of acute episodes that required (1)emergency department use, (2) hospitalizations, (3) urgentcare physician visits for asthma in the past 12 months, and/or(4) steroid bursts.

Interference from asthma. Interference with normal activ-ity was measured using the child activities subscale of the

Children’s Health Survey for Asthma.26 An average of the 5items ranging from 1 (totally limited) to 5 (not at all limited)was calculated for each child.26

Pulmonary function. Spirometry was measured usinga SpiroPro spirometer (Jaeger, a subsidiary of VIASYSHealthcare/CardinalHealth, Conshohocken, Pennsylvania)and a standardized protocol based on the American ThoracicSociety/European Respiratory Society.27 References for spi-rometry values were determined using age, standing height,sex, and ethnicity.28 Results were used to calculate the controland severity scores per NAEPP guidelines.

BMI. Children’s weights were measured with their shoesoff using a calibrated digital scale, and standing height wasmeasured using a stadiometer. BMI (calculated as weight inkilograms divided by height in meters squared) was calcu-lated with adjustments for age and sex based on the Centersfor Disease Control and Prevention growth charts.29 AdjustedBMI levels were then grouped into obese or nonobese.

Controller medication use. Medication use was collectedby caregiver report and subsequently coded as dichotomousvariables, indicating use of any controller medication in thepast 14 days.

Caregiver VariablesAsthma and smoking. Caregiver’s asthma status was dichot-omously coded (yes/no) based on whether they reported everhaving been told by a physician or nurse that they hadasthma. Smoking was evaluated by asking if they “nowsmoke cigarettes every day, some days, or not at all?” Thisvariable was dichotomously coded (yes/no), grouping thosewho responded that they smoke every day or some days assmokers.

Depression. Symptoms of depression in caregiverswas measured using the Center for Epidemiologic Studies–Depression (CES-D) scale, which is a 20-item screening tooldesigned for the general population.30 The CES-D scoresrange from 0 to 60, with a cutoff of 16 or higher suggestiveof depression. The Cronbach � is 0.89 in patients and 0.87 inhealthy adults.

Stress. Caregiver stress was measured using the PerceivedStress Scale (PSS), which is a 10-item self-report measurethat assesses the degree to which life situations are appraisedas overwhelming, unpredictable, and uncontrollable.31,32 Thetimeframe was the past 7 days. Scores range from 0 to 40,with higher scores reflecting more stress. Higher PSS scoreshave been associated with increased rates of upper respiratorytract infections, worse adherence to antiretroviral therapy,and slower wound healing compared with those with lowerPSS scores.31,33,34 Cronbach � reliability coefficients rangefrom 0.75 to 0.92.31,33

Social support. Asthma-specific social support was mea-sured by asking the caregiver “whether or not they could usemore support with their child’s asthma or if they had justabout the right amount of support now.” This item wasdeveloped specifically for the CHIRAH study because wecould find no measure in the published literature that ad-

VOLUME 103, NOVEMBER, 2009 387

dressed this exact construct for caregivers of children withasthma.

Outcome Variables: Asthma Control and Asthma SeverityAsthma control and asthma severity were operationalizedusing the NAEPP/EPR-3 guidelines, which specify compos-ite levels of asthma control and severity based on daytimesymptoms, nighttime awakenings due to symptoms, activitylimitations, use of short-acting �2-agonists for symptom con-trol, lung function, and acute exacerbations.21

Children who took any controller medications in the last 14days were included in the asthma control analyses becauseNAEPP/EPR-3 stipulates that control is the degree to whichsymptoms are minimized by intervention.21 They were clas-sified into 1 of 3 levels of control (well controlled, not wellcontrolled, and poorly controlled). Asthma severity was eval-uated only in children not taking a controller medication inthe past 14 days because the guidelines stipulate that intrinsicintensity of asthma is measured in patients who are nottaking controller medications.21 This group was classifiedinto 2 levels of severity (intermittent/mild or moderate/severepersistent).

Statistical AnalysesThe relationships between variables of interest and dichoto-mous asthma severity and control variables were evaluatedusing Pearson �2, Wilcoxon rank sum, and t tests for dichot-omous, ordinal, and continuous variables, respectively. Lo-gistic regression was used to identify predictors of controland severity separately. For each outcome, 2 models wereconducted. Model 1 included child variables: age, sex, race/ethnicity, and BMI. Model 2 added the following caregivervariables: income, education, asthma and smoking status,depression symptoms, stress, and support. In all models,robust variance estimators were computed to account forwithin-school clustering of study participants. All analyseswere performed using Stata, version 9.2 (StataCorp, CollegeStation, Texas).

RESULTSThe 531 dyads were composed of 303 African Americanchildren and 136 Hispanic/Latino children. The remaining 92children, designated white/other, were 84 white (91%) and 8Asian. Children in our sample had a mean (SD) age of 10.6

Table 1. Characteristics of the Sample by Subgroups and Totala

CharacteristicsControl sample

(n � 294)Severity sample

(n � 237)All participants

(n � 531)

ChildrenAge, mean (SD), y 10.5 (1.8) 10.6 (1.9) 10.6 (1.8)Female 42.2 41.4 41.8Race/ethnicity

Hispanic/Latino 28.2 22.4 25.6African American 54.8 59.9 57.1White/other 17.0 17.7 17.3

Obese 38.4 33.8 36.4Insurance

Private 54 42 48Medicaid or KidCare 45 53 49Uninsured 1 5 3

CaregiversAge, mean (SD), y 38.0 (8.2) 38.3 (7.9) 38.1 (8.1)Education

�High school graduate 12.2 14.8 13.4High school/GED graduate 66.7 70.0 68.2College graduate 21.1 15.2 18.4

Household income�$15,000 19.7 22.7 21.1$15,000-$30,000 23.5 31.7 27.1$30,000-$50,000 20.4 17.3 19.0�$50,000 36.4 28.3 32.8

Have asthma 39.8 33.3 36.9Smoke 29.6 38.4 33.5CES-D score, mean (SD) (range, 0–60) 14.1 (11.8) 13.9 (11.0) 14.0 (11.5)Perceived stress scale score, mean (SD) (range, 0–20) 9.1 (4.3) 9.3 (4.1) 9.2 (4.2)Want more support 38.8 32.5 36.0

Abbreviations: CES-D, Center for Epidemiologic Studies–Depression; GED, general educational development.a Data are presented as percentage of participants unless otherwise indicated. Individuals in the control sample reported using a controllermedication in the past 14 days and are unique from the individuals in the severity sample, who denied controller use.


(1.8) years and 42% were girls. Only 3% of the children wereuninsured, 49% had Medicaid or state insurance, and 48%had private insurance. One hundred ninety-three (36.4%) ofall children in the sample were obese. Caregivers were mostlyfemale (94%), with a mean (SD) age of 38.1 (8.1) years.Approximately 20% of caregivers graduated college and 70%had graduated from high school, with the remaining havingless than a high school education. Our sample was largelylow income, with approximately half the households report-ing a combined income below $30,000 per year.

Of the 531 dyads considered in this study, 237 had nottaken a controller medication in the past 14 days and wereincluded in the severity analyses. The remaining 294 had

taken a controller medication in the past 14 days and wereincluded in the control analysis. Additional characteristicsand summaries by groups are reported in Table 1.

Bivariate AnalysesUnadjusted bivariate comparisons by asthma control andseverity are given in Table 2 and Table 3. Significantly higherrates of poorly controlled asthma were found in obese (P �.02), Hispanic/Latino, and African American children (P �.001). Children with well-controlled asthma were older (P �.002), had caregivers with lower stress levels (P � .005), andhad caregivers who reported that they had sufficient supportwith their child’s asthma (P � .003). Statistically significant

Table 2. Level of Asthma Control by Child and Caregiver Characteristics in 294 Study Participants

Characteristics Finding P value

ChildrenAge, mean (SD), y .002

Age in those with poorly controlled asthma 10.2 (0.1)Age in those with well-controlled asthma 10.9 (0.1)

Poorly controlled asthma group, %Weight .02

Obese 57.5Nonobese 43.1

Sex .76Female 47.6Male 49.4

Race/ethnicity �.001Hispanic/Latino 44.6African American 57.8Other 26.0

CaregiversPoorly controlled asthma group, %

Education .23�High school graduate 50.0High school/GED graduate 51.0College graduate 40.3

Household income, $ �.001�15,000 58.615,000–30,000 60.930,000–50,000 50.0�50,000 34.6

Asthma status .15Have asthma 53.9Do not have asthma 45.2

Smoking status .49Smoke 51.7Do not smoke 47.3

Support status .003Want more support 59.7Have enough support 41.7

CES-D score in poorly controlled asthma group, mean (SD) 15.5 (1.0) .05CES-D score in well-controlled asthma group, mean (SD) 12.8 (0.9)PSS score in poorly controlled asthma group, mean (SD) 9.9 (0.4) .005PSS score in well-controlled asthma group, mean (SD) 8.5 (0.3)

Abbreviations: CES-D, Center for Epidemiologic Studies–Depression; GED, general educational development; PSS, Perceived Stress Scale.


differences were noted in groups based on race/ethnicity andincome levels as well. Less caregiver education and moredepressive symptoms were associated with more severeasthma (P � .02 and P � .006, respectively).

Asthma ControlAs indicated in Table 4, the multivariate logistic models forasthma control were fairly stable across the 2 models. Threesignificant child characteristics were associated with poorasthma control in model 1 (child variables only) and model 2(child plus caregiver variables): obesity, younger age, andbeing African American. The only caregiver variable thatreached statistical significance in model 2 was caregiverstress levels, although it was marginally significant. Higherstress was associated with a 9% increase in the odds of having

poor asthma control. Interestingly, the caregiver variablesminimally altered the association between obesity and poorasthma control, with an odds ratio (OR) close to 2.0 in bothmodels. In fact, the child variable most affected by adding thecaregiver variables was ethnicity. African American childrenwere more likely to have poor asthma control without con-sidering the influence of caregiver variables. This associationdecreased from an OR of 3.09 (95% confidence interval [CI],1.63–5.84) to an OR of 2.1 (95% CI, 1.05–4.46) with addi-tion of the caregiver variables but remained significant in thefinal model.

Asthma SeverityAs indicated in Table 5, the variables associated with asthmaseverity were significantly changed by adding the caregiver

Table 3. Level of Asthma Severity by Child and Caregiver Characteristics in 237 Study Participants

Characteristics Finding P value

ChildrenAge, mean (SD), y .67

Age in moderate/severe asthma group 10.6 (0.1)Age in mild/intermittent asthma group 10.5 (0.2)

Moderate/severe asthma group, %Weight .07

Obese 61.3Nonobese 49.0

Sex .81Female 54.1Male 52.5

Race/ethnicity .04Hispanic/Latino 58.5African American 56.3Other 35.7

CaregiversModerate/severe asthma group, %

Education .02�High school graduate 65.7High school/GED graduate 53.6College graduate 38.9

Household income, $ .03�15,000 61.115,000–30,000 57.330,000–50,000 53.7�50,000 41.8

Asthma status .05Have asthma 62.0Do not have asthma 48.7

Smoking status .92Smoke 52.8Do not smoke 53.2

Support status .005Want more support 66.2Have enough support 46.9

CES-D score in moderate/severe asthma group, mean (SD) 15.7 (1.0) .006CES-D score in mild/intermittent asthma group, mean (SD) 11.8 (1.0)PSS score in moderate/severe asthma group, mean (SD) 9.7 (0.3) .07PSS score in mild/intermittent asthma group, mean (SD) 8.7 (0.4)

Abbreviations: CES-D, Center for Epidemiologic Studies–Depression; GED, general educational development; PSS, Perceived Stress Scale.


variables to the model. In model 1 for asthma severity withonly the child variables, African American and Hispanicchildren were more likely to have moderate to severe asthmathan the white children (OR, 2.51 and 2.33, respectively).However, adding the caregiver variables in model 2 made thisrelationship disappear, and having a caregiver in need ofmore asthma-specific support increased the risk of having achild with moderate to severe asthma (OR, 2.07; 95% CI,1.06–4.05).

DISCUSSIONIn this study, we focus on the relationships between child-hood obesity and caregiver psychosocial variables in child-hood asthma. This study contributes to the existing researchby using 2 clinically relevant summary indicators of asthmamorbidity derived from the NAEPP guidelines, namely,asthma control and asthma severity.23

Our results revealed unique patterns of relationships forasthma control vs asthma severity. Poor asthma control wassignificantly associated with obesity, younger age, and beingAfrican American or Hispanic when considering child vari-ables alone. When the caregiver variables were added to themodel, higher perceived stress among caregivers and the 3child risk factors remained significant risk factors. The find-ings of worse asthma control in children who were obese and

of racial/ethnic minority status are consistent with most pub-lished studies,12–14,35 although 2 studies have reported noasthma morbidity discrepancy based on obesity.26,27 In oursample, obesity increased the odds of having poor asthmacontrol by 89%.

Although caring for a child with a chronic illness such asasthma can be a source of stress itself, much of the recentresearch assumes that caregiver stress and depression areadversely affecting childhood asthma.28–40 The National Co-operative Inner-City Asthma Study (NCICAS) recruited1,260 children and their caregivers from 6 cities in the UnitedStates.21 Results revealed that children were significantlymore likely to have been hospitalized for asthma during the9-month follow-up period if their caregivers reported morestressful life events and/or worse mental health. This rela-tionship persisted after controlling for baseline asthma mor-bidity, demographic variables, and additional psychosocialvariables. Unscheduled physician visits for asthma were notsignificantly related to stress or mental health of the caregiverin the NCICAS. In a clinical sample of children with asthma,Shalowitz et al40 reported that caregiver stress and depressionalong with the child’s sex (female) were significantly relatedto the child’s asthma morbidity. Most recently, Wolf et al38

reported that caregivers’ stress and depression at baselinewere associated with children’s inflammatory responses dur-

Table 4. Logistic Regression Models for Asthma Control in 294 Study Participants

Characteristics

Odds ratio (95% confidence interval)

Model 1: childvariables only

Model 2: child andcaregiver variables

ChildrenObese 1.92 (1.23–3.00)a 1.89 (1.17–3.05)a

Age 0.80 (0.70–0.91)a 0.79 (0.69–0.90)a

Female 1.01 (0.63–1.62) 1.12 (0.68–1.86)Race/ethnicity

Hispanic/Latino 1.71 (0.91–3.20) 1.32 (0.62–2.78)African American non-Hispanic 3.17 (1.68–5.99)a 2.16 (1.05–4.46)b

Other 1.00 1.00Caregivers

Education�High school graduate 1.00High school/GED graduate 1.29 (0.55–3.03)College graduate 1.38 (0.45–4.22)

Household income, $�15,00015,000–30,000 1.16 (0.53–2.55)30,000–50,000 0.89 (0.41–1.92)�50,000 0.54 (0.22–1.33)

Have asthma 1.27 (0.80–2.03)Smoke 1.07 (0.59–1.97)CES-D score 0.99 (0.95–1.02)Want more support 1.34 (0.78–2.31)Perceived stress scale score 1.09 (1.01–1.18)b

Abbreviations: CES-D, Center for Epidemiologic Studies–Depression; GED, general educational development.a P � .01.b P � .05.


ing a 6-month period. Although at least 1 other study suggeststhat stress may alter inflammatory pathways to trigger asthmasymptoms in children,41 the study by Wolf et al is the firstlongitudinal study that links caregiver psychosocial statuswith changes in inflammatory markers in children. None ofthese referenced studies included BMI and stress in the anal-yses, although inflammatory pathways are also implicated inobesity.42

One additional comparison with the NCICAS is of interest.In our study, 192 children (36.4%) had a BMI in the 95thpercentile or higher compared with 19%, which was reportedin a secondary analysis of the NCICAS data.13 This largedifference may be explained by the fact that obesity increasesin older children and the children in CHIRAH were 8 to 14years compared with the NCICAS, which included 4- to9-year-olds. An additional factor may be that the 2 studieswere conducted 10 years apart and increases in national rateof childhood obesity may be reflected in the higher number.

Our study addresses associations, not causation or direc-tion. Nonetheless, it is interesting that both caregiver stressand depression symptoms were significant in bivariate anal-yses, whereas only perceived stress remained weakly signif-icant in the multivariate model for asthma control. Our find-ing is generally consistent with the study by Wolf et al, whichexplored the impact of caregiver-perceived stress and depres-sion on children’s immune function during a 6-month period.

Caregiver stress explained 7.2% of the variance in eosinophilcationic protein changes and 7.6% of the variance in inter-leukin 4 level change. Depression was less a factor significantonly for eosinophil cationic protein change, explaining 3.6%of the variance. Hence, Wolf et al38 conclude that stress ismore robust than depression in explaining children’s inflam-matory markers.

Factors associated with asthma severity were less stableacross the 2 models. In model 1, African American andHispanic children were more likely than white children tohave moderate to severe asthma. This relationship lost sig-nificance when the caregiver variables were added in model2. Interestingly, the only significant association that remainedin the full model was caregivers’ desire for more asthma-specific support and asthma severity. We cannot determinefrom these analyses whether the children with more severeasthma contributed to their caregivers’ sense of needing sup-port or whether the caregivers’ lack of support affected theirability to care for the child’s asthma, resulting in worseoutcomes. Surprisingly, little research has explored the rela-tionship between caregiver’s asthma-specific social supportneeds and the child’s asthma status. Studies that includesocial support tend to use generalized social support measuresor social network scales and consider social support as abuffer.43

Table 5. Logistic Regression Models for Asthma Severity in 237 Study Participants

Characteristics

Odds ratio (95% confidence interval)

Model 1: childvariables only

Model 2: child andcaregiver variables

ChildrenObese 1.64 (0.91–2.94) 1.67 (0.91–3.07)Age 1.04 (0.90–1.21) 1.04 (0.89–1.22)Female 1.07 (0.62–1.88) 1.04 (0.54–2.00)Race

Hispanic/Latino 2.51 (1.04–6.09)a 1.92 (0.69–5.34)African American non-Hispanic 2.33 (1.04–5.23)a 1.89 (0.76–4.70)White/other 1.00 1.00

CaregiversEducation

�High school graduate 1.00High school/GED graduate 0.64 (0.30–1.38)College graduate 0.51 (0.19–1.38)

Household income, $�15,000 1.0015,000–30,000 1.12 (0.52–2.41)30,000–50,000 1.01 (0.45–2.27)�50,000 0.86 (0.39–1.88)

Have asthma 1.61 (0.92–2.83)Smoke 0.67 (0.40–1.13)CES-D score 1.02 (0.99–1.05)Want more support 2.07 (1.06–4.05)a

Perceived stress scale score 1.02 (0.95–1.10)

Abbreviations: CES-D, Center for Epidemiologic Studies–Depression; GED, general educational development.a P � .05.


Medication adherence was not a primary outcome inCHIRAH; therefore, we relied on caregiver report for medi-cation use, which is highly susceptible to overreporting.44,45

As a result, some children included in the asthma controlanalyses may not have actually received any controller med-ication in the past 14 days.

Self-report measures of asthma control are 1 component ofthe NAEPP/EPR-3 definition of asthma control. CHIRAHdid not include any such measure because the study beganbefore the widespread use of self-report asthma control mea-sures in children and few validated measures were available.

For most individuals with asthma, severity and controlfluctuate over time. This dynamic nature of asthma makes alongitudinal approach more desirable; therefore, the general-izability of the results are limited.

In conclusion, our findings add to the growing literaturethat suggests that childhood asthma is embedded within thelarger social context of a child’s environment.19 Three poten-tially mutable risk factors for worse asthma outcomes wereidentified in our study: childhood obesity, high levels ofcaregivers’ perceived stress, and limited asthma-specific so-cial support. Simply providing sufficient asthma support andeducation in the clinical setting is sufficiently challenging,not to mention successfully addressing child weight loss oridentifying and addressing caregivers’ stressors.46 Althoughpediatric health care professionals may be many caregivers’most frequent health professional contact,47 the current med-ical environment presents numerous barriers to interveningon caregiver issues.48 As noted by others, meaningful inter-vention to decrease asthma disparities and obesity in childrenwill require action at numerous levels of our society.24,49

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Requests for reprints should be addressed to:Lisa K. Sharp, PhDSection of Health Promotion ResearchDepartment of MedicineUniversity of Illinois at ChicagoWestside Research Office BuildingMC2751747 W Roosevelt RdChicago, IL 60608E-mail: [email protected]


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The influence of caregiver’s psychosocial status on childhood asthma and obesity