Socioeconomic Status and Bronchiolitis Severity Among Hospitalized Infants

Abstract

OBJECTIVE:

To investigate the relationship between socioeconomic factors and bronchiolitis severity among hospitalized infants.

METHODS:

We performed a 17-center, prospective cohort study from 2011 to 2014. Children <1-year old hospitalized with bronchiolitis were enrolled. Socioeconomic factors included estimated median household income (MHI) per home ZIP code, parent- reported household income, number of adults and children in household, and insurance type. We defined higher bronchiolitis severity as receipt of intensive care treatment. Multivariable logistic regression was used to analyze the association between socioeconomic factors and bronchiolitis severity, with the final model adjusted for potential clustering by site.

RESULTS:

In multivariable models adjusted for demographic and clinical characteristics, estimated MHI was the socioeconomic factor most strongly associated with severity. Compared to infants with an intermediate MHI ($40,000 – $79,999), odds of receiving intensive care treatment were significantly higher for those with MHI of >$80,000 (aOR 2.05, 95%CI 1.19–3.53). No significant associations were found for the other socioeconomic factors (all P>0.30). While there were no significant differences in clinical presentation between income groups (all P>0.25) or in receipt of mechanical ventilation alone (P = 0.98), infants with estimated MHI ≥$80,000 were significantly more likely to specifically have been admitted to the intensive care unit (P = 0.01).

CONCLUSIONS:

In this multicenter study of infants hospitalized with bronchiolitis, we identified higher median household income as a risk factor for intensive care treatment. This work may yield important biological or non-biological insights for the future management of infants with bronchiolitis.

Introduction

Bronchiolitis is the leading cause of hospitalization for infants in the United States, with more than 100,000 hospitalizations each year in children under 1 year of age;¹ this represents approximately 3% of all U.S. infants. Bronchiolitis hospitalization costs are more than $500 million annually,² and have seen a 30% increase ($1.34 billion to $1.73 billion) in associated hospital charges from 2000 to 2009.³ Moreover, research has shown that infants hospitalized for bronchiolitis are at significantly increased risk of developing recurrent wheezing and eventual childhood asthma.^4–6 Bronchiolitis, therefore, affects a substantial proportion of the population and is linked to the development of chronic disease in that population.

Studies have found that children with a lower socioeconomic status (SES) are more likely to present to the emergency department (ED) with bronchiolitis, and subsequently be admitted, when compared to the general population.^7–9 Given the impact and cost of bronchiolitis, it is important to determine if SES is independently associated with bronchiolitis severity, both from a health disparities standpoint (i.e., SES-based inequalities in respiratory health) and from a clinical perspective (i.e., the potential of clinical pathways to increase the likelihood of equitable treatment). To address this knowledge gap, we examined data from a multicenter, prospective cohort to identify socioeconomic factors associated with bronchiolitis severity among hospitalized infants.

Methods

Study Design

We conducted a secondary analysis of the 35^th Multicenter Airway Research Collaboration (MARC-35), a multicenter, prospective cohort study coordinated by the Emergency Medicine Network (EMNet; www.emnet-usa.org). Infants hospitalized for bronchiolitis were enrolled for three consecutive fall/winter seasons from 2011–2014 from 17 hospitals across 14 U.S. states.

Evaluation and treatment of patients was done at the discretion of the healthcare providers on site. In each month of enrollment, investigators enrolled patients within 24 hours of admission using a standardized protocol. Inclusion criteria for the study were an attending physician’s diagnosis of bronchiolitis, <1 year of age, a parent/guardian with the ability to give informed consent in English or Spanish, and complete contact information that was not expected to change for at least 12 months. Exclusion criteria were having already enrolled in the study, transfer to a participating hospital >48 hours after original admission, a time >24 hours since having transferred to a participating hospital, parent/guardian who refused collection or future use of biospecimens, insurmountable language barrier, certain chronic conditions (e.g., immunodeficiency, known heart-lung disease), gestational age <32 weeks, or the patient having met the primary endpoint of the initial 5-year grant (U01 AI-087881) at time of enrollment (i.e., 2 or more treatments of corticosteroids in 6 months, or 4 or more episodes of wheezing in one year). Consent and data collection forms were translated into Spanish. All participating hospitals had human subjects approval and local approval of their institutional review board.

Methods of Measurement

Patients were first screened using a brief interview to determine their eligibility. After initial screening, investigators completed a structured interview with parents/guardians to assess patients’ demographic characteristics, history (both medical and environmental), and to obtain detailed information regarding the bronchiolitis episode for which they were admitted. This structured interview contained questions about the socioeconomic factors examined in this analysis, namely home ZIP code (which was used to estimate median household income [MHI] by linking to MHI estimates from Esri Business Analyst Desktop [Esri, Redlands, CA]), parent-reported income per household, number of adults and children in household, and child health insurance type.

Further clinical data on the patient’s evaluation, treatment, and course of illness was obtained via the patient’s medical records, including vitals, respiratory rates, bronchodilator use, clinical assessment of degree of retractions, apnea, wheezing, oxygen saturation, labs, medical management, and disposition. This chart review included the primary outcome of the current analysis, bronchiolitis severity, which was defined as receipt of intensive care treatment (i.e., admission to intensive care unit [ICU] and/or requiring mechanical ventilation).¹⁰ Staff at EMNet Coordinating Center manually reviewed all data for any inconsistencies or missing information and queried the participating hospitals for clarification.

Data Analysis

All analyses were performed using Stata 14.1 (Stata Corp, College Station, TX). Data are presented as proportions with 95% confidence intervals (95%CIs) and medians with interquartile ranges. To examine potential factors associated with bronchiolitis severity, we performed unadjusted analyses using chi-square, Fisher’s exact test, and Kruskall Wallis test, as appropriate. All P-values were two-tailed, with P<0.05 considered statistically significant.

Multivariable logistic regression was used to analyze the independent associations between socioeconomic factors and the primary outcome of bronchiolitis severity. Factors were considered for inclusion in the model if they were found to be suggestively associated with the outcome in unadjusted analyses (P<0.20) or were considered potentially clinically significant. The final regression model was adjusted for demographics, clinical characteristics, and potential clustering by hospital, with results reported as adjusted odds ratios (aORs) with 95%CIs.

We created a separate model combining the two sources of income data (i.e., estimated MHI per ZIP code and parent-reported total household income). This model comprised five combined income data groups: low-low (i.e., both estimated MHI and parent-reported income <$40,000), medium-medium (i.e., both estimated MHI and parent-reported income between $40,000 – $79,999), high-high (i.e., both estimated MHI and parent-reported income ≥$80,000), mixed levels (i.e., estimated MHI and parent-reported income in different brackets), and prefer not to answer/unknown. In order to observe the “true” relationship between MHI per ZIP code and the likelihood of the primary outcome of bronchiolitis severity, we also continuously modeled MHI using locally weighted regression, or loess.¹¹

Estimated MHI was then evaluated across several pre-admission clinical parameters, including the number of days since the index breathing problem began, degree of retractions, presence of apnea, and oral intake by conclusion of the pre-admission visit. We also assessed MHI income groups by individual bronchiolitis severity measures: ICU admission, use of mechanical n, and hospital length of stay (LOS).

To test whether our main findings could be reproduced, we conducted a replication analysis using multivariable logistic regression in MARC-30, a separate and previously reported multicenter cohort of children hospitalized for bronchiolitis for three consecutive winter seasons from 2007–2010.¹² Adjusted results from both cohorts (i.e., MARC-35 and MARC-30) were pooled in a meta-analysis to obtain a combined result. This meta-analysis combined the log odds ratio of each cohort, weighted by the inverse of their variances, using a random effects model. The between-studies heterogeneity was tested using the Q statistic.¹³

Finally, we conducted a post-hoc power calculation to demonstrate that the sample size for the current secondary analysis was not selected specifically to study MHI and intensive care treatment, but rather was based upon the primary hypothesis of MARC-35, which relates to virus type and risk of asthma.

Results

Patient demographics and socioeconomic characteristics are shown in Table 1. In our cohort of 1,016 infants admitted to hospitals for bronchiolitis, the median age was 3.2 months, 60% were male, and 42% were non-Hispanic white. The median MHI, as defined by patient ZIP code, was $47,199. Furthermore, 30% of parents/guardians reported total household income <$40,000; 19% reported between $40,000 and $79,999; and 21% reported ≥$80,000; while 29% either preferred not to answer or did not know the answer to the question. Most households had 2 adults at home (66%), and had at least 1 other child at home (79%). Most infants had public insurance at time of admission (60%).

Table 1.

Demographic and Socioeconomic Characteristics of Infants Hospitalized for Bronchiolitis, by Intensive Care Treatment Status

	Overall (n=1016)	Non-intensive care treatment (n=853)	Intensive care treatment (n=163)
Characteristics	n (%)	n (%)	n (%)	P-value
Age at enrollment in months				<0.001
<2.0 months	311 (31%)	232 (27%)	79 (48%)
2.0–5.9 months	452 (44%)	400 (47%)	52 (32%)
≥6 months	253 (25%)	221 (26%)	32 (20%)
Sex				0.98
Male	610 (60%)	512 (60%)	98 (60%)
Female	406 (40%)	341 (40%)	65 (40%)
Race/ethnicity				0.04
Non-Hispanic white	430 (42%)	367 (43%)	63 (39%)
Non-Hispanic black	239 (24%)	210 (25%)	29 (18%)
Hispanic	308 (30%)	244 (29%)	64 (39%)
Other	39 (4%)	32 (4%)	7 (4%)
Median household income by ZIP code				0.02
<$40,000	357 (35%)	290 (34%)	67 (41%)
$40,000 to $79,999	543 (53%)	472 (55%)	71 (44%)
≥$80,000	116 (11%)	91 (11%)	25 (15%)
Total household income (parent-reported)				0.16
<$40,000	305 (30%)	263 (31%)	42 (26%)
$40,000 to $79,999	198 (19%)	172 (20%)	26 (16%)
≥$80,000	215 (21%)	178 (21%)	37 (23%)
Prefer not to answer/unknown	298 (29%)	240 (28%)	58 (36%)
Number of adults in home, median (IQR)	2 [2–3]	2 [2–3]	2 [2–3]	0.63
Number of adults in home
1	78 (8%)	65 (8%)	13 (8%)
2	674 (66%)	571 (67%)	103 (63%)
≥3	264 (26%)	217 (25%)	47 (29%)
Number of other children at home				0.61
0	209 (21%)	181 (21%)	28 (17%)
1	377 (37%)	317 (37%)	60 (37%)
2	236 (23%)	196 (23%)	40 (25%)
≥3	194 (19%)	159 (19%)	35 (21%)	0.24
Any other children in home	807 (79%)	672 (79%)	163 (83%)	0.22
Insurance				0.59
Private	391 (39%)	327 (38%)	64 (39%)
Public	606 (60%)	511 (60%)	95 (58%)
None	17 (2%)	13 (2%)	4 (2%)
Building where child lives				0.59
Detached house/single family/duplex/row house	705 (69%)	591 (69%)	114 (70%)
Apartment	284 (28%)	241 (28%)	43 (26%)
Other (e.g., trailer)	27 (3%)	21 (2%)	6 (4%)
Ever attended daycare	234 (23%)	214 (25%)	20 (12%)	<0.001
Ever had smoke exposure	156 (15%)	142 (17%)	14 (9%)	0.009

Abbreviations: IQR denotes interquartile range

Table 1 also shows unadjusted associations between patient demographics, socioeconomic characteristics and intensive care treatment. Of the infants enrolled into our cohort, 163 (16%) were considered to have had a very severe bronchiolitis episode, meaning that they were either admitted to the ICU (n=159, 16%) and/or required mechanical ventilation (i.e., receipt of continuous positive airway pressure [CPAP] and/or intubation) (n=55, 5%). There were 51 infants (5%) in our cohort who both were admitted to the ICU and required mechanical ventilation.

Unadjusted associations between clinical characteristics of infants hospitalized for bronchiolitis and intensive care treatment are shown in Table 2. Compared to infants that did not receive intensive care treatment, infants that received intensive care treatment were more likely to have a lower median initial oxygen saturation, moderate to severe retractions at presentation, apnea, and inadequate oral intake by conclusion of the pre-admission visit. The median index hospital LOS for infants who did not require intensive care treatment was 2 days, compared to 4 days for infants who did require intensive care treatment.

Table 2.

Clinical Characteristics of Infants Hospitalized for Bronchiolitis, by Intensive Care Treatment Status

	Overall (n=1016)	Non-intensive care treatment (n=853)	Intensive care treatment (n=163)
Characteristics	n (%)	n (%)	n (%)	P-value
History of breathing problems prior to index	206 (20%)	174 (20%)	32 (20%)	0.82
Number of days since index breathing problem began				0.001
<4 days	566 (56%)	455 (53%)	111 (68%)
≥4 days	450 (44%)	398 (47%)	52 (32%)
Respiratory Syncytial Virus	821 (81%)	686 (80%)	135 (83%)	0.48
Rhinovirus	214 (21%)	180 (21%)	34 (21%)	0.94
Initial oxygen saturation, median (IQR)	96% (94–98%)	96% (94–98%)	95% (90–98%)	<0.001
Initial retractions				<0.001
None	192 (19%)	169 (20%)	23 (14%)
Mild	431 (43%)	393 (46%)	38 (23%)
Moderate/Severe	358 (35%)	260 (31%)	98 (60%)
Not documented	31 (3%)	27 (3%)	4 (2%)
Presence of apnea				<0.001
No or not documented	960 (94%)	820 (96%)	140 (86%)
Yes	56 (6%)	33 (4%)	23 (14%)
By conclusion of pre-admission visit, oral intake was…				<0.001
Adequate	392 (39%)	362 (43%)	30 (18%)
Inadequate	601 (59%)	471 (55%)	130 (80%)
Not documented	20 (2%)	17 (2%)	3 (2%)
Index hospital length of stay ≥3 days	399 (39%)	273 (32%)	126 (77%)	<0.001

Abbreviations: IQR denotes interquartile range

Multivariable analyses of intensive care treatment status among infants hospitalized for bronchiolitis are shown in Table 3. In our final model adjusted for demographic and clinical characteristics, we found that MHI estimated by patient ZIP code was the socioeconomic factor most strongly associated with bronchiolitis severity. Compared to infants with an intermediate MHI ($40,000 - $79,999), those with MHI of <$40,000 may have been more likely to receive intensive care treatment (aOR 1.59, 95%CI 0.91–2.79) and those with MHI of ≥$80,000 were significantly more likely to receive intensive care treatment (aOR 2.05, 95%CI1.19–3.53). Additionally, adjusting for parent-reported household income in the multivariable model did not materially change the result for MHI by ZIP code (result not shown), nor was parent-reported income a significant predictor of intensive care use (all P>0.30). When we included the 29% of participants who preferred not to answer or did not know the answer to the direct question about parent-reported income in multivariable analyses, there was still no association with bronchiolitis severity, suggesting a wide range of income levels for these participants. Similarly, no significant associations were found for the other socioeconomic factors (i.e., number of adults and children in household and insurance type) (all P>0.30), and thus they were not included in the final model. While we observed an association between race/ethnicity and bronchiolitis severity in unadjusted analyses, this association did not persist in the multivariable model (all P>0.10).

Table 3.

Multivariable Model of Intensive Care Treatment among Infants Hospitalized for Bronchiolitis

Characteristics	aOR	95%CI		P
Age at enrollment, months
<2 months	3.56	2.32	5.45	<0.001
2–5.9 months	1.05	0.53	2.08	0.88
6–11.9 months	1.00	reference
Sex
Male	1.00	reference
Female	0.92	0.64	1.34	0.67
Race/ethnicity
Non-Hispanic white	1.00	reference
Non-Hispanic black	0.99	0.67	1.46	0.94
Hispanic	1.69	0.85	3.37	0.14
Other	1.02	0.53	1.96	0.96
Median household income by ZIP code
<$40,000	1.59	0.91	2.79	0.11
$40,000 to $79,999	1.00	reference
≥$80,000	2.05	1.19	3.53	<0.01
Insurance
Private	1.00	reference
Public	0.84	0.59	1.21	0.36
None	0.97	0.30	3.21	0.97
Premature birth (≤37 weeks)	1.35	0.89	2.05	0.16
Number of days since index breathing problem began
<4 days	1.93	1.25	2.97	0.003
≥4 days	1.00	reference
Presence of apnea
No or not documented	1.00	reference
Yes	2.75	0.98	7.67	0.05
Initial retractions
None	1.00	reference
Mild	1.13	0.59	2.18	0.70
Moderate/Severe	3.94	1.96	7.90	<0.001
Not documented	1.31	0.26	6.60	0.74
Initial oxygen saturation	0.90	0.87	0.94	<0.001
By conclusion of pre-admission visit, oral intake was…
Adequate	1.00	reference
Inadequate	3.16	1.61	6.17	0.001
Not documented	0.88	0.09	8.19	0.91

Abbreviations: aOR denotes adjusted odds ratio; CI, confidence interval

Having observed a strong association between estimated MHI per home ZIP code and bronchiolitis severity, we performed a sensitivity multivariable analysis (Supplemental Table 1) combining the two sources of income data into one key exposure variable; infants with high-high income status were at even higher odds of intensive care treatment (aOR 4.20, 95%CI 1.78–9.94) compared to those in the medium-medium group. We found no association between other combined income data groups (i.e., low-low, mixed levels, and prefer not to answer/unknown) and bronchiolitis severity (all P>0.45).

We conducted a loess estimate (Figure 1) to provide rationale for the selected income cutoffs of <$40,000, between $40,000 and $79,999, and >$80,000. The loess estimate suggests that the relationship between MHI and the primary outcome is nonlinear, with the largest increase in the likelihood of intensive care treatment being at higher income levels. While selecting categorical groupings for MHI is a somewhat arbitrary process, we attempted to choose income cutoffs that reflected this non-linear association and were also logical, rounded numbers.

Figure 1.

Loess Estimate of the Likelihood of Intensive Care Treatment as a Function of Median Household Income by ZIP Code

We examined potential differences between MHI groups and infant clinical presentation. However, no associations were found between MHI and number of days since the index breathing problem began, degree of retractions, presence of apnea, and oral intake by conclusion of the pre-admission visit (all P>0.25). As expected, infants with estimated MHI of ≥$80,000 were significantly more likely to have been admitted to the ICU compared to infants with estimated MHI of either <$40,000 or between $40,000 and $79,999 (P = 0.01). There was no difference between income groups in either use of mechanical ventilation alone (P = 0.98) or in median index hospital LOS (P = 0.76).

In a replication analysis using the MARC-30 cohort of 2,207 children younger than 2 years hospitalized with bronchiolitis, we also found that children with MHI of ≥$80,000, compared to those with an MHI of $40,000–$79,999, were significantly more likely to receive intensive care treatment (aOR 1.39, 95%CI 1.01–1.92). Our meta-analysis combining both cohorts also confirmed this result (aOR 1.58, 95%CI 1.10–2.26), and showed a slightly stronger association between MHI of <$40,000 and receipt of intensive care treatment than in the multivariable model with the MARC-35 cohort alone (aOR 1.43, 95%CI 0.98–2.10), with P = 0.23 for heterogeneity suggesting that the two cohorts are comparable.

Through a post-hoc power calculation, we determined a detect our actual result (aOR 2.05, 95%CI 1.19–3.53) for infants with MHI of ≥$80,000 being significantly more likely to receive intensive care treatment, relative to those with an intermediate MHI ($40,000–$79,999).

Discussion

Among 1,016 infants hospitalized for bronchiolitis in the U.S., we found that estimated MHI per home ZIP code was independently associated with bronchiolitis severity. Infants from higher–income families were significantly more likely to have received intensive care treatment for their bronchiolitis, and to specifically have been admitted to the ICU, as compared to lower-income and intermediate-income infants. Lower-income infants may have been more likely than infants from intermediate-income backgrounds to receive intensive care treatment, but the results were not statistically significant.

Although mechanistic research is limited, there are several explanations for how higher income status might increase risk of bronchiolitis severity during infancy. The hygiene hypothesis, first postulated by Strachan in 1989,¹⁴ suggests that reduced microbial exposure in early life may help explain the increased prevalence of asthma and allergic diseases over the past several decades.^15–17 The underlying assumption here is that proper immune system development relies on the presence of infections in early life, which has led some to interpret the hygiene hypothesis as proposing that excessive cleanliness can lead to decreased immune system activation. Perhaps, then, infants living in areas characterized by higher-income ZIP codes are immunocompromised by overly sterile home and community environments, and thus are at increased risk of bronchiolitis severity.

Recent research, however, has moved towards understanding how changes in the human microbiome may influence development of immune function.^16–18 This paradigm shift resulted in part due to the public health importance of communicating that good hygiene is necessary for preventing infectious disease,¹⁶ but largely because data have shown that the early microbial exposures necessary for developing a strong and well-regulated immune system are fundamentally unrelated to the conventional meaning of “hygiene” as perceived by the public.^18,19 Studies have reported associations between the infant intestinal and upper-airway microbiome and bronchiolitis severity, suggesting that the microbiome plays a critical role in protecting against respiratory disease in early life.^20–22 While beyond the scope of this analysis, further research is warranted on how lifestyle differences among high-income individuals might be shaping their infants’ microbiomes in such a way that makes them more susceptible to higher severity episodes of bronchiolitis.²³ Additionally, investigating clinical strategies for complementing or imitating microbial metabolites to help shape the infant immune response may represent a promising new approach for disease prevention.

In terms of differential results for the two sources of income data (i.e., estimated MHI per ZIP code and parent-reported total household income), it is important to note that estimated MHI per home ZIP code is a more multifaceted measure of wealth than parent-reported income alone. There are social and physical characteristics associated with neighborhoods that are unrelated to the monetary wealth of a community,²⁴ and these factors may confound the relationship between income level and bronchiolitis severity. It is beyond the scope of this analysis to comment on such potential confounding variables. However, we encourage future studies to assess how the environmental factors associated with living in wealthy neighborhoods might be interacting with individual-level SES factors to affect respiratory health outcomes.

We must consider our findings in the broader context of the social determinants affecting health inequalities.^25,26 Clearly, SES is not the direct determinant of bronchiolitis severity, but our finding that higher-income infants are at significantly increased risk of intensive care treatment could imply an underlying disparity in the treatment of bronchiolitis. We found no significant differences across income categories in either receipt of mechanical ventilation alone or in index hospital LOS, another proxy measure for bronchiolitis severity.¹² However, our observation that higher income status was strongly associated with ICU admission, and not associated with pre-admission clinical presentation between income groups, is suggestive of differential decision making by SES in favor of admitting higher-income infants to the ICU. This may be explained by wealthier families pushing for admission to the ICU because they know they can afford the “best care” possible, even if their infant’s illness may not be objectively or comparatively severe enough to warrant ICU admission.

It is possible that higher-income infants may be more susceptible to higher severity bronchiolitis episodes that result in increased rates of admission to the ICU. Given the data, however, the more likely explanation is greater healthcare utilization by higher-income families in the context of severe bronchiolitis, despite no differences in physiologic measures of clinical severity. We have previously reported no differences in ICU admission rates for bronchiolitis with respect to income.²⁷ However, given the significant expenditures and staffing requirements associated with ICUs,²⁸ we believe that a closer examination of disparities in the treatment of bronchiolitis may elucidate clinical pathways for optimizing quality of care while reducing healthcare costs and inefficiencies.

Our findings deviate from those of previous studies reporting significant associations between lower estimated MHI per home ZIP code and higher severity bronchiolitis outcomes, namely higher odds of mechanical ventilation use, longer hospital and ICU LOS, and increased hospital charges.^29,30 The current study is novel in that it is the first to demonstrate the relation of higher-income status and bronchiolitis severity. Regardless of the exact mechanism explaining how estimated MHI acts as a risk factor for intensive care treatment, the public health implications of our findings are potentially large. Considering the association between infant bronchiolitis and childhood asthma,^4,5 as well as the tremendous costs of bronchiolitis hospitalization,^2,3 our data should facilitate further research on interventions aimed at mitigating bronchiolitis severity and reducing disparities in care.

Our study has several potential limitations. First, 29% of respondents either opted not to answer or did not know the answer to the direct question about parent-reported total household income. Therefore, we may not have observed a statistically significant association between parent-reported income per household and bronchiolitis severity due to insufficient statistical power. It is possible, though, that parent-reported income could have matched the result for estimated MHI per home ZIP code, had all parents/guardians answered the direct question about income level. Furthermore, our observation that infants with high-high income status were at even greater risk of e care treatment than infants in the high-income group based only on estimated MHI per home ZIP code lends strength to the association between higher-income status, however measured, and bronchiolitis severity.

Also, the structured interview conducted with parents/guardians to assess patients’ demographic characteristics did not include a question about educational level, which is often regarded as a fundamental component of SES.³¹ To address this shortcoming, we added questions about parent/legal guardian educational level to periodic long-term follow-up interviews currently being conducted over telephone by the EMNet Coordinating Center. Eventually, we can use these data to assess the association between educational level and bronchiolitis severity.

Another limitation of the present study is that our sample consisted of infants admitted to urban hospitals; therefore, our inferences may be less generalizable to other settings (e.g., rural or suburban). Moreover, there exists variability across institutions in utilization of CPAP and intubation for children with bronchiolitis unexplained by differences in patient severity.³² However, it is worth noting that the observed association between higher income status and bronchiolitis severity persisted even after we controlled for clinically important covariates and accounted for potential clustering of clinician use of mechanical ventilation between hospitals. Furthermore, our result was bolstered by its confirmation in a separate large, multicenter cohort of children hospitalized for bronchiolitis. While it is necessary to validate the results of our analysis in other studies, we believe that, because of our large sample and racially/ethnically- and geographically-diverse cohort, the observed relationships are likely to appear in other clinical settings.

Conclusions

Based on a large, multicenter, prospective cohort study of infants hospitalized with bronchiolitis, we identified estimated MHI per home ZIP code as a risk factor for intensive care treatment. Specifically, we observed that higher-income status infants were significantly more likely, and lower-income status infants may also have been more likely, to receive intensive care treatment when compared to infants with an intermediate MHI. Our analysis suggests that these associations may operate in part through mechanisms other than those of the biological correlates underlying respiratory illness. These findings should encourage clinicians to adopt care pathways that promote the likelihood of equitable treatment and, subsequently, better respiratory health outcomes. For researchers, our observations lend support to the importance of understanding the impact of social determinants of health.

What’s New.

Infants at most risk of a higher severity hospitalization for bronchiolitis were those from high-income families and who live in high-income neighborhoods. This has several possible explanations, including an underlying socioeconomic disparity in the treatment of severe bronchiolitis.