Abstract
Background.
Social determinants of health are associated with disparate asthma outcomes in school-age children. Social determinants have not been studied in preschool children with recurrent wheezing.
Objective.
We hypothesized that preschool children with recurrent wheezing at highest risk of social vulnerability would have more frequent symptoms and exacerbations when followed over one year, despite receiving standardized and supervised asthma care.
Methods.
A multi-center population of adherent preschool children receiving standardized and supervised care for wheezing was stratified by a composite measure of social vulnerability based on individual-level variables. Primary outcomes included days with upper respiratory infections and days with asthma symptom flares. Other outcomes included symptom scores during upper respiratory infections and respiratory symptom flare days, exacerbation occurrence, quality of life during the exacerbation and hospitalization.
Results.
Preschool children at highest risk of social vulnerability did not have more frequent upper respiratory infections, respiratory symptoms or exacerbations, but instead had more severe symptoms during upper respiratory infections and respiratory flare days, as well as more severe exacerbations with significantly poorer caregiver quality of life. Children at highest risk of social vulnerability also lived in poorer housing conditions with differing exposures and self-reported triggers.
Conclusion.
Individual-level social determinants of health reflecting social vulnerability are associated with poorer outcomes in preschool children with recurrent wheezing despite access to supervised and standardized care. Comprehensive assessment of social determinants of health is warranted in even the youngest children with wheezing, since mitigation of these social inequities is an essential first step toward improving outcomes in pediatric patients.
Keywords: Asthma control, Asthma exacerbation, Disparities, Environmental exposures, Ethnicity, Poverty, Race, Social determinants of health, Wheeze
Introduction
The prevalence of recurrent wheezing among preschool children less than 5 years of age has increased more than two-fold over the past 20 years.1 Consequently, preschool children now account for more than 10% of all children with asthma in the United States1 and are a substantial driver of costs in children.2, 3 Yet despite widespread availability of controller medications, each year, nearly half of all preschool children with recurrent wheezing have a significant exacerbation necessitating medical care.4 Furthermore, compared to older school-age children with asthma, preschool children also have twice the rate of emergency department visits and more than five times the rate of hospitalization for wheezing exacerbations.5, 6
It is increasingly recognized that social determinants of health, defined by the World Health Organization as the non-medical factors that influence health outcomes,7 are important drivers of asthma morbidity in children.8 For example, current asthma prevalence increases as a function of the poverty threshold and is nearly two-fold higher in children below the poverty threshold versus children at 450% of the poverty threshold or higher.1, 6 Similarly, black versus white race and Hispanic/Latino ethnicity have been consistently associated with poorer asthma control and greater healthcare utilization in school-age children.6, 9, 10 However, these associations tend to be oversimplifications since social determinants of health act synergistically to influence health outcomes.11 For example, in separate analyses, more than 80% of the racial disparities in asthma outcomes in school-age children could be explained by other social determinants, including socioeconomic status, neighborhood characteristics, and family hardship.12, 13
Despite the prevalence and public health burden of preschool children with recurrent wheezing, social determinants of health have been largely understudied in this population. Given that preschool children may be particularly vulnerable to their social environments due to their age and their complete caregiver dependency,14 this study compared baseline and longitudinal outcomes in a large, multi-center population of well-characterized and adherent preschool children stratified by a composite measure of social vulnerability based on individual-level variables. We hypothesized that children at highest risk of social vulnerability would have more frequent symptoms and wheezing exacerbations over one year of follow-up despite the receipt of standardized and supervised medical care.
Methods
Baseline and intervention period data were merged from two multi-center clinical trials housed in the National Heart, Lung and Blood Institute’s Biologic Specimen and Data Repository Information Coordinating Center. Each study was a Phase 3 clinical trial involving preschool with recurrent wheezing. Both studies were conducted at the same 15 academic medical centers across the United States. Details of the included studies (i.e., Azithromycin for Preventing the Development of Upper Respiratory Tract Illnesses into Lower Respiratory Tract Symptoms (APRIL, NCT01272635)15 and Individualized Therapy for Asthma in Toddlers (INFANT, NCT01606306))16 were published previously and are shown in Table 1. Briefly, the APRIL study determined whether azithromycin, initiated during an upper respiratory infection, reduced the development of severe lower respiratory tract symptoms in children with a history of virally induced wheezing who were not treated with asthma controller medications. The INFANT study was a randomized crossover of three treatment approaches (daily inhaled fluticasone, daily montelukast, and as-needed inhaled fluticasone) in children with persistent asthma who met criteria for daily asthma controller medication use according to the National Asthma Education and Prevention Panel’s Expert Panel Report.17 Exclusion criteria for each of the studies included premature birth, recent antibiotic or systemic corticosteroid use within the previous 2–4 weeks, or inadequate adherence to diary completion during the study run-in periods. Acceptable adherence was defined by completion of at least 75–80% of the daily diaries. Written informed consent was obtained from all caregivers.
Table 1.
Inclusion criteria for the APRIL and INFANT studies.
| Study feature | APRIL | INFANT |
|---|---|---|
| Years conducted | 2011–2015 | 2013–2015 |
| Participants enrolled | 607 | 300 |
| Age of participants | 12–71 months | 12–59 months |
| Additional requirements in the past year | ≥2 clinically significant wheezing exacerbations1 | Uncontrolled asthma2 |
| Study design | Parallel arm | Cross-over |
| Run-in period | 2–4 weeks | 2–8 weeks |
| Run-in medication3 | No medication | Placebo or open-label ICS or LTRA taken daily |
| Treatment arm duration | 52–78 weeks | 16 weeks |
| Treatment arm interventions | Azithromycin or Placebo administered only during respiratory tract infections | Daily ICS Daily LTRA As-needed ICS |
Defined as a wheezing episode necessitating an urgent care visit, hospitalization, or systemic corticosteroids
Defined as symptoms >2 days per week (previous 2 weeks), nighttime awakening from asthma at least once (previous 4 weeks), ≥4 wheezing episodes within the past year, or ≥2 exacerbations requiring systemic corticosteroids in the preceding 6 months.
Open-label albuterol sulfate was permitted during the run-in for each study
Participant characterization.
Each center was certified and utilized the same manual of procedures for participant characterization. At study entry, caregivers completed demographic and asthma medical history questionnaires. Peripheral blood eosinophils were quantified from whole blood by means of an automated assay at each clinical site. Total and specific IgE levels (ImmunoCAP) were performed for a nationally representative panel of aeroallergens (cat dander [ImmunoCAP test code E1], dog dander [E5], mold mix [Mx1], German cockroach [i6], grass mix [gx2], tree mix [Tx4, Tx6], (9) weed mix [Wx1], giant ragweed [W3], Dermatophagoides pteronyssinus [D2] and Dermatophagoides farinae [D2]) at a central laboratory (St. Louis Children’s Hospital, St. Louis, MO). Tests with levels >0.34 IU/mL were considered positive for sensitization.
After study entry, caregivers in the INFANT study completed daily electronic diaries (Spirotel, Medical International Research, Rome, Italy) for the duration of the study that questioned the presence of any cough, wheeze, difficulty breathing and activity limitation, which were each scored from 0 (absent) to 3 (severe). In the APRIL study, caregivers completed the paper Asthma Flare-Up Diary for Young Children (ADYC) on each day of a caregiver-identified upper respiratory infection for the duration of the study. This tool has 7 items pertaining to specific respiratory symptoms and 10 items pertaining to the degree of problem resulting from symptoms, with each item scored from 1 (not at all) to 7 (worst).18 Items are summed for a cumulative score.18 If the episode progressed to an exacerbation, caregivers completed a 21-item quality of life questionnaire, Effects of a Young Child’s Asthma Flare-up on the Parents (ECAP), with questions focused on caregiver feelings, concerns, and experiences.19 Each item is scored on a scale of 1 (not at all) to 6 (all the time). Items are averaged to obtain a total ECAP score, which assesses the burden of a preschool child’s exacerbation on caregiver functional status.19
Standardization and supervision of asthma care.
At enrollment, all caregivers received a written action plan that detailed instructions for administration of albuterol sulfate (90 mcg/actuation) when a pre-specified threshold of symptoms was met. Albuterol sulfate and a valved holding chamber were provided by the study and were dispensed at the first visit, then as needed at each subsequent study visit. Additionally, caregivers received a home supply of oral prednisolone in the event of an asthma exacerbation that was also dispensed at the first study visit. Children whose symptoms did not resolve or who required albuterol treatments for more than 24 hours were first instructed by action plan to call the study medical staff, who were available by phone 24 hours a day, and then to initiate a 4-day burst of prednisolone (2 mg/kg/day for 2 days followed by 1 mg/kg/day for 2 days). The action plan was reviewed and reinforced with caregivers at each study visit. Physician discretion for prednisolone administration outside of the action plan parameters was also permitted provided that a specific reason for the initiation was documented.
Social vulnerability determination.
Recognizing that social vulnerability is a complex construct, a composite measure of social vulnerability was constructed with four participant-level variables, including self-reported ethnicity, self-reported race, self-reported highest level of household educational attainment, and household poverty. Household poverty was estimated from self-reported annual household income and the reported number of people residing in the household who were supported by the income. Poverty was determined according to the poverty guidelines issued in the Federal Register by the Department of Health and Human Services.20 Each of the four variables was assigned a score as shown in Table 2. The four variable items were summed for a composite score. Groups were designated as “lower risk” (score=0), “moderate risk” (score=1) and “highest risk” (score ≥2).
Table 2.
Social vulnerability composite score.
| Variable | Score |
|---|---|
| Ethnicity | Not Hispanic or Latino = 0 Hispanic or Latino = 1 |
| Race | White = 0 Black, more than one race, or other = 1 |
| Highest household education | Technical training or any education after high school = 0 Did not complete high school, high school degree, or GED = 1 |
| Household poverty | Not below poverty guideline = 0 Below poverty guideline = 1 |
Total score = 0–4
Outcomes.
Primary outcomes included self-reported days with upper respiratory infections and days with respiratory symptom flares. Respiratory symptom flare days were self-reported days with any cough, wheezing, difficulty breathing, or activity limitation. Secondary outcomes included symptom scores during upper respiratory infections, symptom scores on days with respiratory flares, and the occurrence of any exacerbation treated with systemic corticosteroids. Exploratory outcomes included quality of life during the exacerbation and hospitalization. The definition of exacerbation was consistent with that proposed by a National Institutes of Health Working Group21 and was defined as respiratory symptoms resulting in treatment with systemic corticosteroids (prednisolone).
Outcome analyses.
Analyses were performed with IBM SPSS software, version 28. Symptom scores during upper respiratory infections were reflected by cumulative scores on the ADYC instrument. Symptom scores during acute exacerbations were obtained from the sum total of the cough, wheeze, difficulty breathing and activity limitation scores from electronic diaries, with a range of 1 to 12. For each participant, daily responses were averaged to obtain the mean symptom score per participant, which was then compared between groups stratified by social vulnerability risk scores. For quality of life assessments, data from all exacerbations were averaged for each participant. Differences in the baseline features and outcomes of the social vulnerability risk groups were analyzed with Chi-Square tests and analysis of variance, with Tukey least significant differences post-hoc tests. All analyses utilized a 0.05 significance level without adjustment for multiple comparisons.
Results
The sample for analysis consisted of 821 preschool children with recurrent wheezing who had complete outcome data. Features of the children at study entry, stratified by social vulnerability risk, are shown in Table 3. Consistent with the composite definition, the lower risk group was composed of white children with higher household education and income levels. The moderate and highest risk groups had more racial and ethnic diversity, but the highest risk group was further distinguished by lower educational attainment and greater poverty. Housing features also differed in the highest risk group and included greater tobacco smoke exposure, air conditioner, humidifier and dehumidifier access, and more visible cockroaches. Children in the highest risk group also had lesser indoor pet exposure and spent more time in the home, with less daycare attendance. Years spent in the current home was not significantly different between groups (mean ± standard error of the mean, lower risk: 3.53 ± 0.21; moderate risk: 3.46 ± 0.20; highest risk: 3.27 ± 0.30, p=0.765).
Table 3.
Demographic and household features of the participants, by social vulnerability. Data represent the mean ± standard error of the mean or the number of participants (%).
| Lower risk N=253 |
Moderate risk N=403 |
Highest risk N=165 |
|
|---|---|---|---|
| Study | |||
| APRIL | 163 (64.4) | 279 (68.9) | 109 (63.7) |
| INFANT | 90 (35.6) | 124 (30.6) | 61 (35.7) |
| Age (years) | 2.8 ± 0.1 | 3.0 ± 0.1 | 2.9 ± 0.1 |
| Male | 143 (56.5) | 266 (65.7)* | 88 (52.1)^ |
| Race | |||
| Black | - | 165 (40.9)* | 76 (46.1)* |
| White | 253 (100) | 191 (47.4) | 75 (45.5) |
| Other | - | 47 (11.7) | 14 (8.5) |
| Hispanic ethnicity | - | 108 (26.8)* | 58 (35.2)*^ |
| Highest household education | |||
| Did not complete high school | - | 5 (1.2)* | 28 (17.0)*^ |
| High school diploma | - | 30 (7.4) | 93 (56.4) |
| Technical training | 5 (2.0) | 22 (5.5) | 9 (5.5) |
| Some college (did not graduate) | 96 (37.9) | 162 (40.2) | 29 (17.5) |
| College degree | 152 (60.1) | 184 (45.7) | 6 (3.6) |
| Combined annual household income | |||
| <$25,000 | 32 (12.6) | 104 (25.8)* | 142 (86.1)*^ |
| $25,000 – $49,999 | 52 (20.6) | 139 (34.5) | 20 (12.1) |
| $50,000 – $99,999 | 91 (36.0) | 97 (24.1) | 3 (1.8) |
| $100,000 or more | 78 (30.8) | 63 (15.6) | |
| Number of people in the household | 3.9 ± 0.1 | 3.7 ± 0.2 | 4.3 ± 0.1 *^ |
| Housing features | |||
| Tobacco smoke | 55 (21.7) | 117 (29.0)* | 54 (32.7)* |
| Air conditioner | 196 (77.5) | 314 (77.9) | 105 (63.6)*^ |
| Humidifier | 118 (46.6) | 169 (41.9) | 37 (22.4)*^ |
| Dehumidifier | 64 (25.3) | 68 (16.9)* | 6 (3.6)*^ |
| Visible cockroaches | 27 (10.7) | 50 (12.4) | 38 (23.0)*^ |
| Indoor cats | 59 (23.3) | 59 (14.6)* | 18 (10.9)* |
| Indoor dogs | 107 (42.3) | 117 (29.0)* | 30 (18.2)*^ |
| Daycare attendance | 150 (59.3) | 226 (56.1) | 63 (38.2)*^ |
p<0.05 vs. lower risk,
p<0.05 vs. moderate risk
Baseline respiratory and allergic features.
Respiratory and allergic features of the participants at study entry are shown in Table 4. Children at highest risk of social vulnerability had an earlier age of respiratory symptom onset and were significantly more likely to have a sibling also diagnosed with asthma. Asthma medication use and wheezing-related healthcare utilization in the past year were not different between groups (number of systemic corticosteroid bursts, mean ± standard error of the mean, lower risk: 1.24 ± 0.08; moderate risk: 1.32 ± 0.07; highest risk: 1.11 ± 0.10, p=0.220; number of emergency department visits, lower risk: 2.67 ± 0.12; moderate risk: 2.70 ± 0.10; highest risk: 2.62 ± 0.15, p=0.905). However, children at highest risk reported significantly more respiratory symptom triggers (mean ± standard error of the mean, lower risk: 3.77 ± 0.12; moderate risk: 3.93 ± 0.09; highest risk: 4.93 ± 0.13, p<0.001) which included chemical and environmental exposures. Highest risk children also had lesser sensitization to cats and dogs but greater sensitization to cockroaches. Total serum IgE concentrations were also slightly elevated in children at highest risk, but this was not accompanied by an increase in blood eosinophils.
Table 4.
Asthma and allergic features of the participants, by social vulnerability. Data represent the mean ± standard error of the mean or the number of participants (%).
| Lower risk N=253 |
Moderate risk N=403 |
Highest risk N=165 |
|
|---|---|---|---|
| Age of asthma symptom onset (months) | 15.2 ± 0.8 | 13.6 ± 0.5 | 11.3 ± 0.7* |
| Asthma family history | |||
| Parent with asthma | 138 (54.5) | 227 (56.3) | 81 (49.1) |
| Sibling with asthma | 63 (24.9) | 132 (32.8)* | 75 (45.5)*^ |
| Eczema (ever) | 127 (50.2) | 229 (56.8) | 88 (53.3) |
| Asthma medications (any use, past year) | |||
| Inhaled corticosteroid | 133 (52.6) | 193 (47.9) | 80 (48.5) |
| Months used | 2.5 ± 0.2 | 2.3 ± 0.2 | 2.8 ± 0.3 |
| Leukotriene receptor antagonist | 30 (11.9) | 59 (14.6) | 16 (9.7) |
| Exacerbation history (past year) | |||
| Systemic corticosteroid burst | 163 (64.4) | 272 (67.5) | 104 (63.0) |
| Emergency department visit | 231 (91.3) | 380 (94.3) | 153 (92.7) |
| Asthma triggers (self-reported) | |||
| Exercise/exertion | 106 (41.9) | 172 (42.7) | 98 (59.4)*^ |
| Chemicals | 66 (26.1) | 103 (25.6) | 68 (41.2)*^ |
| Weather changes | 173 (68.4) | 305 (75.7)* | 154 (93.3)*^ |
| Cold air | 115 (45.5) | 223 (55.3)* | 126 (76.4)*^ |
| Tobacco smoke | 44 (17.4) | 93 (23.1) | 63 (38.2)*^ |
| Aeroallergen sensitization | |||
| Cat | 51 (20.8) | 88 (22.5) | 18 (11.4)*^ |
| Dog | 60 (24.7) | 101 (25.8) | 25 (15.7)*^ |
| Cockroach | 18 (7.4) | 40 (10.3) | 28 (17.9)*^ |
| Dust mite | 38 (15.5) | 73 (18.6) | 29 (18.1) |
| Weed | 28 (11.7) | 59 (15.5) | 28 (18.1) |
| Mold | 30 (12.4) | 50 (13.1) | 20 (13.0) |
| Grass | 23 (9.5) | 48 (12.4) | 28 (17.6) |
| Tree | 34 (14.1) | 59 (15.4) | 24 (15.4) |
| Positive aeroallergens (number of 8) | 1.2 ± 0.1 | 1.3 ± 0.1 | 1.3 ± 0.2 |
| Total serum IgE (kU/L) | 172 ± 22.4 | 203 ± 24.1* | 277 ± 46.7* |
| Blood eosinophil count (cells/microliter) | 328 ± 18.4 | 358 ± 14.9 | 304 ± 20.4 |
p<0.05 vs. lower risk,
p<0.05 vs. moderate risk
Outcomes.
After study entry, participants completed a run-in period of 2–8 weeks prior to the study intervention. During the run-in period, there was no difference in the average number of days per week with respiratory symptoms between the social vulnerability risk groups (mean ± standard error of the mean, lower risk: 0.88 ± 0.07; moderate risk: 0.90 ± 0.06; highest risk: 0.77 ± 0.09, p=0.449). At the completion of this run-in period, study intervention assignments were made and were not different between groups (APRIL study, percent of participants randomized to azithromycin, lower risk: 50.9%; moderate risk: 51.5%; highest risk: 47.7%, p=0.798; INFANT study, percent of participants first randomized to daily fluticasone, lower risk: 32.9%; moderate risk: 35.2%; highest risk: 25%, p=0.660).
During the study observation period after interventions were assigned, the number of upper respiratory infections was not different between social vulnerability risk groups (mean ± standard error of the mean, lower risk: 1.95 ± 0.08; moderate risk: 1.98 ± 0.06; highest risk: 1.98 ± 0.12, p=0.946). There were also no differences in the total number of days with symptoms related to upper respiratory infection (Figure 1A). However, the average daily symptom score during an upper respiratory infection (i.e, cumulative score on the ADYC instrument) was significantly higher (i.e., worse) in children in the highest risk group (Figure 1B). This difference persisted after adjustment for the APRIL study treatment allocation (adjusted p=0.016 for highest versus lower risk, adjusted p=0.004 for highest versus moderate risk). Individual items on the ADYC instrument that distinguished the highest risk group were more “gasping for air” (question score mean ± standard error of the mean, lower risk: 1.25 ± 0.05; moderate risk: 1.28 ± 0.03; highest risk: 1.49 ± 0.09, p=0.009), more “skin pulling in the neck/throat” (1.21 ± 0.05 vs. 1.22 ± 0.03 vs. 1.38 ± 0.08, p=0.035), and “responds less well to albuterol” (1.67 ± 0.08 vs. 1.68 ± 0.06 vs. 2.11 ± 0.16, p=0.007). Likewise, although the percentage of days with asthma symptoms during the study observation period was not different between groups (Figure 1C), children in the highest risk group had significantly higher cumulative asthma symptom scores on days with respiratory symptom flares (Figure 1D). This difference also persisted after adjustment for the INFANT study treatment allocation (adjusted p=0.015 for highest versus lower risk, adjusted p=0.041 for highest versus moderate risk). Individual items that distinguished the highest risk group were the severity of wheezing (question score mean ± standard error of the mean, lower risk: 0.39 ± 0.04; moderate risk: 0.52 ± 0.05; highest risk: 0.65 ± 0.08, p<0.009), the severity of “trouble breathing” (0.48 ± 0.04 vs. 0.63 ± 0.05 vs. 0.70 ± 0.08, p=0.023), and the severity of activity interference (0.47 ± 0.04 vs. 0.56 ± 0.05 vs. 0.68 ± 0.08, p=0.050). The number of inhalations of albuterol sulfate taken during the 24-hour period of an asthma flare was not significantly different between groups (mean ± standard error of the mean, lowest risk: 2.80 ± 0.15; moderate risk: 2.64 ± 0.14 vs. 2.69 ± 0.24, p=0.759).
Figure 1.
(A) Days with upper respiratory infection (URI) symptoms, (B) severity of URI symptoms, (C) days with asthma-like symptoms, and (D) severity of asthma-like symptoms in children with lower (blue), moderate (yellow), and highest (red) risk of social vulnerability. Higher symptom scores reflect more severe symptoms. Boxplots whiskers represent the 5th and 95th percentile.
Other outcomes are shown in Figure 2. Exacerbation outcomes were available for all participants (lower risk, N=253; moderate risk, N=403; highest risk, N=165). The occurrence of any exacerbation treated with systemic corticosteroids during the study observation period was not different between social vulnerability risk groups (Figure 2A). The average number of exacerbations during the observation period was also not different (mean ± standard error of the mean: lower risk: 0.49 ± 0.06; moderate risk: 0.48 ± 0.04; highest risk: 0.44 ± 0.06, p=0.795). However, children at highest risk of social vulnerability had a greater occurrence of overnight hospitalization during an acute exacerbation compared to the other groups (Figure 2A). In the subset of caregivers who completed the ECAP quality of life measure during acute exacerbation, quality of life scores were significantly poorer (i.e., higher) in the group with highest risk of social vulnerability (Figure 2B). Caregivers of children at highest risk also reported significantly more overall impact (i.e, higher item score) from the asthma exacerbation (Figure 2C). Other specific concerns reported by these caregivers included concerns about not being able to control the exacerbation, difficulty with assessing the severity of the exacerbation, a prolonged stay at a healthcare facility, and risks and side effects of the asthma rescue medication (Table 5).
Figure 2.
(A) Exacerbation outcomes, (B) caregiver quality of life score during the exacerbation, and (C) overall impact on caregivers during the exacerbation in children with lower (blue), moderate (yellow), and highest (red) risk of social vulnerability. Higher scores reflect poorer quality of life and more significant impact. Boxplots whiskers represent the 5th and 95th percentile.
Table 5.
Quality of life responses on the ECAP instrument during acute exacerbation, by social vulnerability. For each participant, data from all exacerbations were averaged. Results represent the mean score per group ± standard error of the mean.
| Response (range: 0 = not at all, 6=extremely) |
Lower risk N=21 |
Moderate risk N=26 |
Highest risk N=14 |
|---|---|---|---|
| I was concerned about not being able to control the asthma flare up at home | 2.81 ± 0.21 | 2.85 ± 0.36 | 3.86 ± 0.54* |
| I was concerned about having difficulty assessing the severity of the asthma flare-up | 2.19 ± 0.36 | 2.81 ± 0.37 | 3.50 ± 0.48* |
| I was concerned about a possibly long stay in the emergency department, at the clinic, or at the hospital | 1.67 ± 0.35 | 2.04 ± 0.38 | 3.29 ± 0.61* |
| I was concerned about the risk of giving my child too much medication | 1.38 ± 0.36 | 2.00 ± 0.40 | 3.21 ± 0.68* |
| I was concerned about the side effects of the medications used to control the flare-up | 1.81 ± 0.36 | 2.23 ± 0.41 | 3.21 ± 0.60* |
p<0.05 vs. lower risk
Discussion
In this analysis of preschool children with recurrent wheezing enrolled in two large, Phase 3, multi-center clinical trials, a higher risk of social vulnerability was associated with significantly poorer longitudinal outcomes despite receipt of standardized and supervised respiratory care. Contrary to our hypothesis, preschool children at highest risk of social vulnerability did not have more frequent respiratory symptoms or exacerbations, but instead had more severe symptoms during upper respiratory infections and during days with respiratory symptom flares and more severe exacerbations with significantly poorer caregiver quality of life when exacerbations occurred. Children at highest risk of social vulnerability also lived in poorer housing conditions with differing exposures and self-reported triggers. These observations highlight the important impact of social determinants of health on outcomes in preschool children with asthma, even despite attempts to mitigate differences in access to care through provision of asthma action plans, rescue medications for exacerbations, 24-hour telephone support, and ongoing education about asthma and rescue medication use.
Social determinants of health have been well recognized for their role in pediatric health outcomes. At the community level, greater neighborhood social vulnerability has been associated with increased odds of preterm birth and neonatal morbidity,22 frequent (i.e., ≥4 per year) acute care visits in children,23 and higher rates of hospitalizations for pediatric conditions that could have been managed with effective outpatient care, including asthma.24, 25 At the level of the individual, social determinants of health have also been linked to less preventative care and greater reliance on emergency care services in children.26 Differences in these social determinants of health ultimately lead to health disparities. For example, racial and ethnic disparities12, 13 and disparities in income and hardship27–30 have been well described in school-age children with asthma and are associated with significantly poorer outcomes, which can be mitigated with multicomponent management programs.31
Given the deidentified nature of the data available for this analysis, we were unable to assess social determinants of health at the community (i.e., census tract or neighborhood) level. Instead, we constructed a composite definition of social vulnerability at the individual patient level that avoids the oversimplification of stratification by single variables, such as race or poverty status, which covary with a variety of other social determinants. The findings within the identified group of children at higher risk of social vulnerability, namely poorer housing conditions and more “brittle” asthma-like features, are biologically plausible. Indoor exposures such as tobacco smoke have been consistently associated with a higher risk of wheeze onset before 2 years,32 as well as more wheezing symptoms and exacerbations in children with existing asthma.33 Likewise, indoor cockroach allergen concentrations increase with greater maternal hardship30 and have been associated with persistent elevation of Type2 inflammatory cytokines in preschool children that are further associated with development of asthma by age 7 years.34 Multicomponent indoor allergen-reduction interventions that include pest control have also been shown to reduce exacerbations, albeit with no effect on discrete outcomes of emergency department utilization and hospitalization.35 Furthermore, indoor air pollutants such as polycyclic aromatic hydrocarbons, particulate matter, and volatile and semi-volatile organic compounds are also increased in homes with natural ventilation, smoking, and frequent use of solvents or household products.36 These pollutants have similarly been associated with an increased risk of asthma onset and reduced asthma control in children,37 presumably through formation of toxic oxidative and/or biologically reactive products that induce epigenetic changes and promote inflammation.38
To our knowledge, this is the first study to address individual-level social determinants of health and prospective outcomes in a multi-center population of preschool children with recurrent wheezing across the United States. While our findings are similar to those previously observed in school-age children with asthma,8 important strengths of the present study include the comprehensive phenotypic characterization and prospective evaluation of the participants, all of whom had documented adherence to the study procedures. This enabled detection of more subtle symptoms and non-emergent exacerbations, whereas the majority of prior studies have focused on system-level emergent visits or hospital admissions. Another important strength is the standardization and supervision of respiratory care, since suboptimal prescribing has been well documented in high-risk, inner city populations of children with asthma.39, 40
Nonetheless, this study does have limitations. First, the composite definition of social vulnerability that was used does not adequately address all of the variables in the World Health Organization’s conceptual framework for social determinants of health, including structural determinants (i.e., governance, macroeconomic policies, housing policies, and public policies), racism, material circumstances such as the neighborhood features and food insecurity, and psychosocial factors such as childhood adversity and community violence.11 Unfortunately, the deidentified data obtained for the present also prohibited adequate assessment of community-level social determinants, which have been addressed in other studies through geospatial mapping approaches.25 Furthermore, although this study attempted to eliminate access to care issues through the provision of asthma action plans, asthma medications, and 24-hour direct telephone support, access to care barriers such as access to a primary care provider may still have existed and could have influenced the symptom and exacerbation outcomes in this study. For example, it is unclear how many of the exacerbations were managed by a primary care provider or an emergency healthcare provider versus the study teams.
It is also possible that patients with the greatest social vulnerability did not use their asthma controller medication as frequently as they reported, or alternatively, were sub-optimally treated. Indeed, this may be supported by the greater fear of giving too much medication and potential side effects. It is also possible that the daily asthma severity of patients with greatest y was incorrectly perceived given the the higher number of self-reported triggers and greater fear of incorrectly assessing the severity of the asthma flare-up in this group. Furthermore, because social determinants of health also coexist and interact, we also cannot rule out residual confounding from other unmeasured determinants. Generalizability of these results to larger populations is also cautioned, since clinical trials select for certain behaviors, such as adherence, telephone and transportation access, and promptness to appointments. Therefore, differences in effect sizes may be substantially larger in real-world populations. The fact that these studies were conducted at academic medical centers also decreases generalization to more rural populations, where access to care and other material circumstances could differ greatly. Differences in outcome measures between the APRIL and INFANT studies is also another limitation.
In summary, the results of this study demonstrate that individual-level social determinants of health that reflect social vulnerability are associated with poorer outcomes in preschool children with recurrent wheezing despite access to supervised and standardized medical care. Although causality cannot be inferred, these observations may be related to the poorer housing conditions and daily exposures of the highest risk participants. Comprehensive assessment of social determinants of health is therefore warranted in even the youngest children, since mitigation of these social inequities is an essential first step toward improving respiratory outcomes in pediatric patients.
Highlights.
What is already known about this topic? (word count = 34)
Preschool children have a significant burden of wheezing. Although social determinants of health have been implicated in disparate asthma outcomes in school-age children, these determinants have not been studied in preschool children with recurrent wheezing.
What does this article add to our knowledge? (word count = 30)
Preschool children at highest risk of social vulnerability have significantly poorer longitudinal respiratory outcomes, including more severe symptoms and more severe exacerbations, despite receipt of standardized and supervised respiratory care.
How does this study impact current management guidelines? (word count = 34)
Comprehensive assessment of social determinants of health is warranted in even the youngest children with recurrent wheezing. Mitigation of these social inequities is an essential first step toward improving respiratory outcomes in pediatric patients.
Acknowledgments
This study was supported in part by: R01 NR017939, K24 NR018866, and UL 1TR002378
Abbreviations
- ADYC
Asthma Flare-Up Diary for Young Children
- APRIL
Azithromycin for Preventing the Development of Upper Respiratory Tract Illnesses into Lower Respiratory Tract Symptoms
- ECAP
Effects of a Young Child’s Asthma Flare-up on the Parents
- INFANT
Individualized Therapy for Asthma in Toddlers
Footnotes
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Author Disclosures: Abby D. Mutic, David T. Mauger, Jocelyn R. Grunwell, Cydney Opolka, and Anne M. Fitzpatrick have no disclosures pertaining to the submitted work.
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