OBJECTIVES

To identify associations between weight category and hospital admission for lower respiratory tract disease (LRTD), defined as asthma, community-acquired pneumonia, viral pneumonia, or bronchiolitis, among children evaluated in pediatric emergency departments (PEDs).

METHODS

We performed a retrospective cohort study of children 2 to <18 years of age evaluated in the PED at 6 children’s hospitals within the PEDSnet clinical research network from 2009 to 2019. BMI percentile of children was classified as underweight, healthy weight, overweight, and class 1, 2, or 3 obesity. Children with complex chronic conditions were excluded. Mixed-effects multivariable logistic regression was used to assess associations between BMI categories and hospitalization or 7- and 30-day PED revisits, adjusted for covariates (age, sex, race and ethnicity, and payer).

RESULTS

Among 107 446 children with 218 180 PED evaluations for LRTD, 4.5% had underweight, 56.4% had healthy normal weight, 16.1% had overweight, 14.6% had class 1 obesity, 5.5% had class 2 obesity, and 3.0% had class 3 obesity. Underweight was associated with increased risk of hospital admission compared with normal weight (odds ratio [OR] 1.76; 95% confidence interval [CI] 1.69–1.84). Overweight (OR 0.87; 95% CI 0.85–0.90), class 1 obesity (OR 0.88; 95% CI 0.85–0.91), and class 2 obesity (OR 0.91; 95% CI 0.87–0.96) had negative associations with hospital admission. Class 1 and class 2, but not class 3, obesity had small positive associations with 7- and 30-day PED revisits.

CONCLUSIONS

We found an inverse relationship between patient weight category and risk for hospital admission in children evaluated in the PED for LRTD.

The prevalence of overweight, obesity, and severe obesity is increasing for children in the United States.1  Lower respiratory tract diseases (LRTDs), including asthma, bronchiolitis, community-acquired pneumonia (CAP), and viral pneumonia, are common reasons for children to seek care in pediatric emergency departments (PEDs). Studies assessing associations between child weight and asthma outcomes have been inconsistent; little is known about associations with severity of other LRTDs in children presenting to the PED.25  Limitations in physical examination, impaired lung function, higher baseline inflammation, and provider obesity bias could all affect clinical outcomes for children with obesity.68  In contrast, malnutrition or underlying comorbidities could contribute to poor clinical outcomes for children with underweight being evaluated for LRTD.9 

Studies using administrative data suggest increased severity of respiratory disease in children with obesity. These studies are well powered but are focused on hospitalized children only and rely on diagnostic coding for obesity, which underestimates obesity prevalence and could introduce ascertainment bias.1015  On the other hand, single-site studies use measured anthropometrics to ensure appropriate weight categorization but may be underpowered and less generalizable.1620  PEDSnet is a database combining electronic health record data, including measured anthropometrics, from 6 geographically diverse major children’s health systems, which could help address these issues in the existing literature.21 

Our objective is to identify associations between weight status and hospital admission in children evaluated in PEDs for LRTD. We hypothesize that underweight, overweight, and obesity will be positively associated with hospital admission compared with normal weight. Our secondary outcomes are 7- and 30-day PED revisits.

We performed a retrospective cohort study using electronic health record data from 6 children’s health systems across the United States that participate in the PEDSnet clinical research network.21  The institutional review board at an academic children’s hospital deemed this study exempt from human subjects review.

The cohort included children 2 to <18 years old evaluated for LRTD, defined as a discharge diagnosis of bronchiolitis, viral pneumonia, asthma, or CAP, in the PED between January 1, 2009, and November 30, 2019. In a separate manuscript (unpublished observations), the authors evaluated the associations of LRTD outcomes with weight category in hospitalized children. Discharge diagnosis codes of interest were identified from International Classification of Diseases, Ninth Revision (ICD-9) codes, which were translated to Systematized Nomenclature of Medicine Clinical Terms codes (Supplemental Tables 2 and 3).22  We excluded children younger than 2 years because of lack of consistent definitions for weight categories for this age group and excluded children older than 17 years because this population is often not admitted to children’s hospitals.23  We excluded children missing height and weight measurements within 3 months of the PED visit. Finally, we used the Pediatric Medical Complexity Algorithm Version 3.0 to exclude those with medical complexity because of anticipated effects of underlying diagnoses on weight status.24 

We obtained clinical, demographic, and anthropometric data from the PEDSnet database. Primary exposure was weight status. We calculated each patient’s BMI from height and weight recorded in the PED; if either value was missing, we accepted the closest available recorded height or weight within 3 months of that PED visit to minimize selection bias. We used age, sex, and BMI to categorize weight status per Centers for Disease Control and Prevention guidelines: <fifth percentile, underweight; fifth percentile to <85th percentile, normal weight; 85th percentile to <95th percentile, overweight; 100% to <120% of 95th percentile, class 1 obesity; 120% to <140% of 95th percentile, class 2 obesity; and ≥140% of 95th percentile, class 3 obesity.23,25,26  Outliers were excluded by Centers for Disease Control and Prevention guidelines.27  Age was categorized as 2–5 years, 6–11 years, and 12–18 years. Payer was categorized as private/military, public, or none. Primary outcome was hospital admission; secondary outcomes were 7- and 30-day PED revisits.

Descriptive statistics determined the prevalence of underweight, normal weight, overweight, and obesity by demographic and clinical characteristics. χ2 tests or analysis of variance procedures were performed as appropriate. We modeled hospital admission, 7-day PED revisits, and 30-day PED revisits using multivariable mixed-effects logistic regression, which included site and patient as random effects and age, sex, race and ethnicity, and payer as covariates. A 2-sided P value of .05 was considered statistically significant. Given incomplete payer data at one site due to electronic health record migration, we performed a sensitivity analysis with all payer data from that site set to missing. We used SAS version 9.4 (SAS Institute, Inc, Cary, NC) for all analyses.

Of 258 709 patients with at least 1 PED visit for LRTD during 2009 and 2019, our final cohort included 107 446 children with 218 180 PED encounters, as shown in Fig 1. Demographic and clinical characteristics are shown in Table 1. At the time of the PED visit, 4.5% had underweight, 56.4% had normal weight, 16.1% had overweight, 14.6% had class 1 obesity, 5.5% had class 2 obesity, and 3.0% had class 3 obesity. PED visits for children with underweight were more likely to include an infectious LRTD discharge diagnosis (bronchiolitis, CAP, or viral pneumonia) compared with those for children of other weight categories. Nearly half of PED encounters for children with underweight resulted in hospital admission, higher than any other weight category.

FIGURE 1

Cohort identification. ED, emergency department.

FIGURE 1

Cohort identification. ED, emergency department.

Close modal
TABLE 1

Demographic and Clinical Characteristics of the Full Cohort at the Encounter Level

Underweight (n = 9755), n (%)Normal Weight (n = 123 033), n (%)Overweight (n = 35 028), n (%)Class 1 Obesity (n = 31 896), n (%)Class 2 Obesity (n = 11 975), n (%)Class 3 Obesity (n = 6493), n (%)P
Age at visit, y       <.01 
 2–5 5994 (61.5) 56 939 (46.3) 13 078 (37.3) 11 446 (35.9) 1903 (15.9) 511 (7.9) — 
 6–11 2507 (25.7) 40 358 (32.8) 12 784 (36.5) 11 733 (36.8) 4232 (43.7) 2617 (40.3) — 
 12–18 1254 (12.9) 25 736 (20.9) 9166 (26.2) 8717 (27.3) 4840 (40.4) 3365 (51.8) — 
Male sex 6065 (62.2) 71 445 (58.1) 19 288 (55.1) 17 829 (55.9) 6212 (51.9) 3339 (51.4) <.01 
Race and ethnicity       <.01 
 White 3549 (36.4) 39 659 (32.2) 10 062 (28.7) 8246 (25.9) 2857 (23.9) 1438 (22.2) — 
 Black 3601 (36.9) 54 060 (43.9) 16 101 (46.0) 14 983 (47.0) 5860 (48.9) 3734 (57.5) — 
 Hispanic 1229 (12.6) 17 497 (14.2) 5817 (16.6) 5930 (18.6) 2297 (19.2) 890 (13.7) — 
 Asian or Pacific Islander 499 (5.1) 3107 (2.5) 551 (1.6) 518 (1.6) 176 (1.5) 65 (1.0) — 
 Other 877 (9.0) 8710 (7.1) 2497 (7.1) 2219 (7.0) 785 (6.6) 366 (5.6) — 
Insurancea       <.01 
 Private or military 3002 (30.8) 32 938 (26.8) 8012 (22.9) 6377 (20.0) 2200 (18.4) 1072 (16.5) — 
 Public 5456 (55.9) 73 522 (59.8) 22 135 (63.2) 20 979 (65.8) 7860 (65.6) 4111 (63.3) — 
 None 761 (7.8) 8813 (7.2) 2627 (7.5) 2442 (7.7) 1016 (8.5) 710 (10.9) — 
Any infectious diagnosisb 2238 (22.9) 13 659 (11.1) 2552 (7.3) 2187 (6.9) 494 (4.1) 230 (3.5) <.01 
Primary asthma diagnosis 4265 (43.7) 56 967 (46.3) 15 946 (45.5) 14 756 (46.3) 5368 (44.8) 2829 (43.6) <.01 
Hospital admission 4356 (44.7) 37 631 (30.6) 9489 (27.1) 8586 (26.9) 3254 (27.2) 1816 (28.0) <.01 
Underweight (n = 9755), n (%)Normal Weight (n = 123 033), n (%)Overweight (n = 35 028), n (%)Class 1 Obesity (n = 31 896), n (%)Class 2 Obesity (n = 11 975), n (%)Class 3 Obesity (n = 6493), n (%)P
Age at visit, y       <.01 
 2–5 5994 (61.5) 56 939 (46.3) 13 078 (37.3) 11 446 (35.9) 1903 (15.9) 511 (7.9) — 
 6–11 2507 (25.7) 40 358 (32.8) 12 784 (36.5) 11 733 (36.8) 4232 (43.7) 2617 (40.3) — 
 12–18 1254 (12.9) 25 736 (20.9) 9166 (26.2) 8717 (27.3) 4840 (40.4) 3365 (51.8) — 
Male sex 6065 (62.2) 71 445 (58.1) 19 288 (55.1) 17 829 (55.9) 6212 (51.9) 3339 (51.4) <.01 
Race and ethnicity       <.01 
 White 3549 (36.4) 39 659 (32.2) 10 062 (28.7) 8246 (25.9) 2857 (23.9) 1438 (22.2) — 
 Black 3601 (36.9) 54 060 (43.9) 16 101 (46.0) 14 983 (47.0) 5860 (48.9) 3734 (57.5) — 
 Hispanic 1229 (12.6) 17 497 (14.2) 5817 (16.6) 5930 (18.6) 2297 (19.2) 890 (13.7) — 
 Asian or Pacific Islander 499 (5.1) 3107 (2.5) 551 (1.6) 518 (1.6) 176 (1.5) 65 (1.0) — 
 Other 877 (9.0) 8710 (7.1) 2497 (7.1) 2219 (7.0) 785 (6.6) 366 (5.6) — 
Insurancea       <.01 
 Private or military 3002 (30.8) 32 938 (26.8) 8012 (22.9) 6377 (20.0) 2200 (18.4) 1072 (16.5) — 
 Public 5456 (55.9) 73 522 (59.8) 22 135 (63.2) 20 979 (65.8) 7860 (65.6) 4111 (63.3) — 
 None 761 (7.8) 8813 (7.2) 2627 (7.5) 2442 (7.7) 1016 (8.5) 710 (10.9) — 
Any infectious diagnosisb 2238 (22.9) 13 659 (11.1) 2552 (7.3) 2187 (6.9) 494 (4.1) 230 (3.5) <.01 
Primary asthma diagnosis 4265 (43.7) 56 967 (46.3) 15 946 (45.5) 14 756 (46.3) 5368 (44.8) 2829 (43.6) <.01 
Hospital admission 4356 (44.7) 37 631 (30.6) 9489 (27.1) 8586 (26.9) 3254 (27.2) 1816 (28.0) <.01 

—, not applicable.

a

Missing insurance data from 14 147 (536 underweight, 7760 normal weight, 2254 overweight, 2098 class 1 obesity, 899 class 2 obesity, and 600 class 3 obesity).

b

Bronchiolitis, CAP, or viral pneumonia documented as either a primary or secondary discharge diagnosis.

Our primary outcome was hospital admission, which occurred in 29.9% of PED evaluations overall. After multivariable mixed-effects logistic regression, underweight had a positive association with hospital admission (odds ratio [OR] 1.76; 95% confidence interval [CI] 1.69–1.84) compared with normal weight. In contrast, overweight, class 1 obesity, and class 2 obesity all had slight negative associations with hospital admission, as shown in Fig 2. These findings persisted in a sensitivity analysis performed to account for missing insurance data at a single site.

FIGURE 2

A–D, Associations after multivariable mixed-effects logistic regression modeling between BMI category and hospital admission (A), hospital admission in a sensitivity analysis for issues with insurance data at a single site (B), 7-day PED revisits (C), and 30-day PED revisits (D).

FIGURE 2

A–D, Associations after multivariable mixed-effects logistic regression modeling between BMI category and hospital admission (A), hospital admission in a sensitivity analysis for issues with insurance data at a single site (B), 7-day PED revisits (C), and 30-day PED revisits (D).

Close modal

Our secondary outcomes were 7- and 30-day PED revisits (Fig 2). We found small positive associations between 7-day revisits and class 1 obesity (OR 1.07; 95% CI 1.01–1.14) and class 2 obesity (OR 1.12; 95% CI 1.02–1.23). Findings were similar for 30-day revisits, except there were significant associations with overweight (OR 1.04; 95% CI 1.00–1.08) as well as class 1 obesity (OR 1.10; 95% CI 1.05–1.15) and class 2 obesity (OR 1.18; 95% CI 1.10–1.26).

In this large cohort representing multiple children’s hospitals across the United States, underweight was associated with increased hospital admission among children evaluated in the PED for LRTD. In contrast to our hypothesis, overweight, class 1 obesity, and class 2 obesity had slight negative associations with hospital admission. We found only small positive associations with 7- and 30-day PED revisits for patients with class 1 and class 2 obesity.

The outcome of hospital admission could represent increased severity of illness.5,16,28,29  Studies from both developed and developing countries have revealed associations between malnutrition and severity of respiratory tract infections, which could be related to immune system effects.9,30  Notably, vitamin D deficiency has been associated with severe respiratory tract infections.31,32  In our study, we assessed underweight rather than specific nutrition or micronutrient deficiencies; however, this association may be an important area of further research. Underweight specifically has been associated with severe illness in Japanese children hospitalized for bronchiolitis and influenzalike illness.33,34  In one multisite study in the United States, both underweight and obesity were associated with measures of asthma severity; hospitalization was not considered as an outcome in that study. Understanding the mechanisms behind our findings could help improve clinical outcomes for this population.

The need for hospital admission could vary with other factors in addition to illness severity. It could reflect health care use, specifically in terms of use of the PED. Patients with more limited health care access may use the PED more frequently, resulting in a larger denominator of children seeking care and a lower percentage who require hospital admission. Obesity is more prevalent among households with lower income and lower education, which could have implications for access to health care; existing studies on differential PED use by children with obesity reveal conflicting results.3537  We did not specifically assess access to care in this study. Hospital admission could also reflect decision-making by PED physicians that is unrelated to illness severity, including social concerns or physician biases, which were not specifically assessed here.

Our large multicenter cohort displays many similarities to descriptions of the general US population. We found similar disparities in weight category by age and race and ethnicity as have been demonstrated previously.1  The prevalence of overweight and class 1 obesity is slightly lower than in the general pediatric population; this likely reflects the younger age of our cohort, which has been described previously in children being treated for LRTD.1  The geographic diversity of our sites may enhance the generalizability of our results.

Several limitations apply to this study. Although multiple hospitals contributed data to the study, all are academic children’s hospitals, which does not reflect all PEDs providing care to children. Missing anthropometric data excluded approximately half of all potential encounters in the PEDSnet database. Although we anticipate that these missing data would most likely bias our results toward the null hypothesis because of likely exclusion of more children with relatively normal height and weight, it should still be considered in interpretation of our results. BMI and BMI categorization do not fully capture body composition or adiposity. Because of the focus of this study on patient BMI category, we excluded children <2 years old, which represents a large population of children with LRTD, especially bronchiolitis. We did not account for asthma severity in this analysis, which could affect these results. Socioeconomic status and health care use are represented only with payer in this data set; other social barriers to health were not captured.

In this multicenter cohort study, hospital admission for LRTD is positively associated with underweight and negatively associated with overweight and obesity in children seeking care in the PED. Further study should be focused on mechanisms behind this finding as a next step to improving clinical outcomes.

Dr Halvorson conceptualized and designed the study, performed the analysis, drafted the initial manuscript, and reviewed and revised the manuscript; Dr Saha, and Ms Razzaghi assisted with data analysis and interpretation and reviewed and revised the manuscript; Drs Forrest, McCrory, Skelton, Wells, Poehling, and Tieder assisted in study design and data interpretation and reviewed and revised the manuscript; Drs Rao, Phan, Magnusen, and Mejias assisted in data acquisition and reviewed and revised the manuscript; and all authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

FUNDING: No external funding.

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Competing Interests

POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.

FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.

Supplementary data