Skip to main content
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2026 Mar 10.
Published in final edited form as: Neurogastroenterol Motil. 2026 Mar;38(3):e70279. doi: 10.1111/nmo.70279

National medical expenditures associated with pediatric disorders of gut-brain interaction in the United States

Ayesha C Sujan 1, Janos Major 2,3, Cornelius B Groenewald 1, Jennifer A Rabbitts 1
PMCID: PMC12969732  NIHMSID: NIHMS2151031  PMID: 41795129

Abstract

Background:

Limited research has evaluated national medical expenditures associated with pediatric disorders of gut-brain interaction (DGBI), despite the high prevalence of these disorders in children and their association with reduced quality of life.

Methods:

We used data from the 2017–2022 Medical Expenditure Panel Survey (MEPS) to estimate the individual and national-level outpatient, office based, prescribed medication, emergency room, inpatient, and other medical expenditures, and overall expenditures associated with pediatric DGBI. Pediatric DGBI included International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10) codes associated with irritable bowel syndrome, functional dyspepsia and other functional intestinal disorders (including constipation) among 40,067 individuals ≤ 18 years receiving medical care in the United States.

Key Results:

After controlling for predisposing factors, enabling resources, and co-morbid medical conditions, total per patient annual medical expenditures was $5,217 (in 2022 dollars) for pediatric patients with DGBI – an estimate that was $2,587 greater than the estimated medical expenditures for children without DGBI. Incremental spending from DGBI patients versus patients without DGBI was highest for outpatient visits followed by office-based visits, prescribed medications, and emergency room visits. Total annual medical expenditures for pediatric patients with DGBI was estimated at $2.08 billion.

Conclusions and Inferences:

The results illuminate the significant national medical expenditures associated with pediatric DGBI, suggesting the potential importance of early detection and effective treatment for pediatric DGBI and the need for future research to improve assessment and evidence-based treatment for pediatric DGBI.

Keywords: Functional gastrointestinal disorder, Pediatrics, Health expenditures

INTRODUCTION

Globally, 23% of youth have disorders of gut-brain interaction (DGBI), as reported in a recent meta-analysis. Functional constipation, functional dyspepsia, and irritable bowel syndrome are the most common pediatric DGBI conditions with prevalence estimates of 12%, 5%, and 3%, respectively.1 Rates of DGBI are increasing over time with marked increases occurring around the time of the COVID-19 pandemic.2 The high prevalence and increasing rates of these conditions are particularly concerning due to the burden associated with these conditions. DGBI symptoms cause significant suffering and reductions in quality of life.3,4 Several studies have documented significant medical utilization and expenditures associated with DGBI, though these studies are limited to narrow samples,5–7 exclude the most common DGBI (i.e., functional constipation),5–7 and estimate only hospitalization expenditures.8,9

Therefore, the aim of the present study was to determine the comprehensive incremental expenditure related to the most common pediatric DGBI utilizing nationally representative data. The current analyses used data from the 2017–2022 Medical Expenditure Panel Survey (MEPS). We estimated individual and national-level overall medical expenditures associated with functional constipation, functional dyspepsia, irritable bowel syndrome, and other functional intestinal disorders among individuals 18 years or younger. A secondary aim was to examine outpatient, office based, prescribed medication, emergency room, inpatient, and other medical expenditures. We hypothesized that children with DGBI, compared to those without, would have higher estimated incremental medical expenditures related to their DGBI after adjusting for predisposing, enabling, and needs factors.

METHODS

Data source

We conducted secondary analysis of data from the 2017–2022 MEPS, representing the 6 most recent years of available data. The MEPS are large-scale, cross-sectional surveys conducted annually by the Agency for Health Research and Quality (AHRQ). The primary purpose of MEPS is to provide the most complete source of data on the costs and utilization of medical care and insurance coverage among the noninstitutionalized civilian population in the United States. The primary respondents were adult members of the household who reported on their child’s medical care utilization, expenditures, insurance coverage, and medical conditions. Following the household interview, MEPS staff then reached out to participants’ medical providers, insurance providers, and employers across the United States to supplement, verify, and/or replace information provided by household respondents about the charges, payments, and sources of payment associated with specific medical encounters and conditions. Medical conditions were coded by professional coders into the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10) codes. For confidentiality, MEPS collapses 5-digit ICD-10 codes to 3-digit ICD-10 codes. Additional information about the MEPS is available online at https://meps.ahrq.gov/mepsweb/.

Study population

The cohort for our study included children 0 to 18 years of age captured in MEPS from January 1, 2017 to December 31, 2022 (n = 40,067), as part of a nationally representative sample of the U.S. population residing in households or other non-institutionalized settings (e.g., homeless shelters). Our institutional review board deemed this study exempt from review due to the de-identified data.

Definition of pediatric DGBI

Participants were classified as having DGBI if they had the following 3-digit ICD-10 codes: K30 “functional dyspepsia”, K58 “irritable bowel syndrome”, and K59 “other functional intestinal disorders”. The K59 code includes constipation, functional diarrhea, neurogenic bowel – not otherwise classified, megacolon – not otherwise classified, and other/unspecified functional intestinal disorders. This group represents individuals seeking medical care for the treatment of DGBI during the previous 12 months. Our control group consisted of participants without these ICD-10 codes.

Primary outcomes: Medical Expenditures

MEPS provides expenditure data on total, as well as specific medical services used by participants during the previous 12 months. Our primary outcome was total medical expenditures, which included hospital-based outpatient visits, office-based visits, emergency department visits, inpatient stays, prescription medications, home health care visits, and a category of “other” medical expenditures (disposable supplies, long-term equipment, ambulance use, vision, and dental visits). Secondary outcomes included service specific medical expenditures. Expenditures included participants’ out-of-pocket expenditures and payments from public and private health insurance. We did not include over-the-counter medications as these are not captured by MEPS.

The sources of expenditures captured included the 3 main sources of medical expenditures on child health in the United States, including payments from private insurance, payments from public health insurance, and out-of-pocket payments. We also included a category of other combined expenditures, which although rare among children, includes expenditures by Medicare, military sources, other state and local sources, and other unclassified sources. To allow for comparable estimates across 2017–2022, all expenditures were inflated to 2022 dollars, using the Personal Health Care Price Index as recommended by MEPS.10

Covariates

The Andersen Behavioral Model of Health Service Use10 specifies covariates for inclusion in studies of medical care expenditures. According to this model, medical care expenditures are influenced by predisposing factors, enabling resources, and need factors. Predisposing factors are demographic characteristics including age, sex, race and ethnicity, and geographic region that exist before health conditions. Enabling factors represent resources that facilitate (or impede) medical care use, and we included insurance status, and poverty status. Need factors refer to co-morbid medical conditions influencing the perceived or evaluated need for medical care, and for this we included co-morbid physical and mental medical conditions. To classify children’s health conditions into a meaningful variable, we used the Pediatric Comorbidity Index (PCI),11 a validated score developed to summarize disease burden and adjust for confounding in pediatric epidemiologic studies using medical claims data. It includes 24 categories of pediatric-specific conditions, including: alcohol abuse, anemia, anxiety, malignancy, asthma, cardiovascular conditions, chromosomal anomalies, congenital malformations, depression, developmental delays, diabetes, drug abuse, eating disorders, epilepsy/convulsions, gastrointestinal conditions, pain, smoking, psychotic disorders, weight loss, conduct disorders, joint disorders, menstrual disorders, and nausea/vomiting. Each condition was weighted based on its association with 1-year risk of hospitalization, and the PCI outperformed adult comorbidity indices and the Pediatric Medical Complexity Algorithm (C-statistic = 0.718). PCI is a practical tool for summarizing pediatric health status and improving risk adjustment in real-world data studies.

Data Analysis Plan

Analyses were conducted using the survey package contained in Stata version 19.0 (StataCorp College Station, TX). The threshold for statistical significance was p < 0.05 and our hypothesis testing was two-tailed. We adjusted for the complex sample design of MEPS by using sampling weights, regional stratification, and primary sampling unit information to provide nationally representative estimates for the population in the United States. We used descriptive statistics to summarize sociodemographic and clinical characteristics comparing children with and without DGBI. Group differences were estimated using Rao-Scott adjusted Chi-square tests for categorical variables and design-based t-tests for continuous variables.

To address our primary aim of estimating medical expenditures associated with pediatric DGBI, we isolated the effect of DGBI on expenditures by estimating the difference between estimated expenditures if an average child had DGBI compared to expenditure for an average child without DGBI. This difference was also referred to as incremental expenditures. We specified models to calculate the incremental medical expenditures associated with DGBI, controlling for age, sex, race, ethnicity, geographical region, insurance, income category, as well as PCI score.

Characteristics of medical expenditure data typically include being highly skewed and including large numbers of zero expenditures. Therefore, in deciding the best models to use for our data analysis, we considered the following 4 modelling approaches: a) two-part models with logistic regression for the first part and generalized linear regression (GLM) with a log link function and Gamma distribution for the second part, b) two-part models with logistic regression for the first part and GLM with a square root link function and Gamma distribution for the second part, c) GLM with a log link function and Gamma distribution, and d) simple ordinary least squares (OLS) regression models of medical expenditures using GLM models with specified link function and distribution. Goodness of fit testing revealed that our data was best with an OLS regression model. Supplemental figure 1 demonstrates residual plots for each fitted model, with OLS clearly showing the best fit. We checked potential multicollinearity by calculating the variance inflation factors (VIFs), with VIFs <5 indicating low or no significant multicollinearity. We repeated this procedure for each expenditure outcome finding no multicollinearity. Given these findings, we used OLS regression to estimate associations between pediatric DGBI and medical expenditures, controlling for age, sex, race, ethnicity, geographical region, insurance, income category, and PCI score throughout all our analyses.

Finally, the national medical expenditures associated with DGBI were determined by multiplying the overall incremental expenditures per individual with DGBI by the number of individuals with DGBI, which was estimated directly from MEPS by applying sampling weights.

RESULTS

Sample demographics

The sample contained 40,067 children between the ages of ​​0 and 18 years of age participating in the 2017–2022 MEPS. Mean age of children in the sample was 9.2 years, with the study population being predominantly male (51.0%), White, non-Hispanic (49.1%), having some private insurance (60.7%), and being more likely to be from the Southern region of the United States (39.0%), which is consistent with the demographics of the pediatric population in the United States.

In this sample, 445 (1.1% (95% Confidence Interval (CI): 0.9–1.3%)) reported seeking medical care for pediatric DGBI. Several groups were overrepresented in the DGBI cohort, including females, children reporting their race/ethnicity as white, non-Hispanic, and those in the poor/near poor income category. Children with pediatric DGBI had on average, greater PCI scores relative to controls – 0.9 (95% CI: 0.7–1.2) versus 0.3 (95% CI: 0.3–0.3) (Table 1).

Table 1.

Sample sociodemographic factors

Total sample DGBI No DGBI p-value
% 95% CI % 95% CI % 95% CI
Age (mean) 9.2 (9.1,9.4) 8.1 (7.4,8.8) 9.2 (9.1,9.4) <0.001
Sex
Male 51.0 (50.1,51.9) 41.8 (35.7,48.2) 51.1 (50.2,52.0) 0.005
Female 49.0 (48.1,49.9) 58.2 (51.8,64.3) 48.9 (48.0,49.8)
Race/Ethnicity
White, non-Hispanic 49.1 (46.8,51.4) 54.2 (47.6,60.8) 49.0 (46.7,51.3) 0.485
Black, non-Hispanic 13.8 (12.3,15.4) 11.8 (7.9,17.3) 13.8 (12.3,15.4)
Hispanic 25.6 (23.3,28.0) 23.2 (18.4,28.7) 25.6 (23.3,28.0)
Asian, non-Hispanic 5.4 (4.5,6.3) 4.3 (2.5,7.3) 5.4 (4.5,6.3)
Other, non-Hispanic 6.2 (5.6,7.0) 6.5 (4.2,10.0) 6.2 (5.6,6.9)
Insurance coverage
Any private 60.7 (58.5,62.7) 52.3 (45.4,59.2) 60.7 (58.6,62.8) 0.003
Public only 36.8 (34.8,38.8) 46.6 (39.8,53.4) 36.7 (34.7,38.7)
Uninsured 2.6 (2.2,3.0) 1.1 (0.4,3.4) 2.6 (2.2,3.0)
Income category
Poor/near poor 21.3 (20.0,22.7) 27.8 (22.6,33.6) 21.2 (19.9,22.7) 0.088
Low income 15.1 (14.2,15.9) 15.4 (11.2,20.8) 15.1 (14.2,15.9)
Middle income 29.9 (28.8,31.0) 28.1 (22.9,34.0) 29.9 (28.8,31.1)
High income 33.7 (31.9,35.7) 28.7 (22.3,36.1) 33.8 (31.9,35.7)
Region
Northeast 15.9 (13.7,18.4) 16.9 (11.4,24.4) 15.9 (13.7,18.4) 0.178
Midwest 21.1 (18.3,24.2) 26.1 (20.5,32.6) 21.0 (18.2,24.1)
South 39.0 (35.4,42.6) 32.0 (25.4,39.3) 39.0 (35.5,42.7)
West 24.1 (21.0,27.5) 25.1 (19.3,31.9) 24.1 (21.0,27.5)
Pediatric Comorbidity Index (mean) 0.3 (0.3,0.3) 0.9 (0.7,1.2) 0.3 (0.3,0.3) <0.001

Note: Sample percentages are weighted. CI=confidence interval. DGBI=Disorders of gut-brain interaction.

The mean total medical expenditures per child across the entire sample was $2,657 (95% CI: $2,450-$2,864) per year. Of note, there were no significant differences in medical expenditures per child by year, with all years ranging between $2,464 (lowest in 2020) and $2,734 (highest in 2017). The unadjusted total medical expenditures for a child with pediatric DGBI was $6,570, which was significantly greater than the unadjusted total medical expenditures for controls: $2,616 (data not presented in tables).

Adjusted medical expenditures associated with pediatric DGBI

Given significant differences in the pediatric DGBI as compared to controls (Table 1), we conducted adjusted analysis to determine associations between pediatric DGBI and total medical expenditures as described in our statistical analysis section. Over and above predisposing, enabling, and need factors, total yearly medical expenditures for pediatric patients with DGBI ($5,217, 95% CI: $3,987-$6,448) was significantly higher than controls ($2,630, 95%CI: 2,431–2,828) with a total incremental yearly cost associated with pediatric DGBI of $2,587 (95% CI: $1,318-$3,857). Yearly incremental expenditures were significantly higher for DGBI patients compared to controls for outpatient visits ($450, 95% CI: $149-$751), office-based visits ($385, 95% CI: $0-$770), prescribed medications ($374, 95% CI: $32-$717), and emergency room visits ($170, 95% CI: $78-$261) (Table 2).

Table 2.

Adjusted mean annual estimated medical expenditures of pediatric patients with DGBI versus those without.

Pediatric DGBI (A)
$ (95% CI)
Controls (B)
$ (95% CI)
Incremental expenditures associated with pediatric DGBI (A-B)
$ (95% CI)
p-value
Total 5217 (3987,6448) 2630 (2431,2828) 2587 (1318,3857) <0.0001
Outpatient 1316 (1024,1609) 866 (815,916) 450 (149,751) 0.003
Office based 626 (270,982) 241 (155,327) 385 (0,770) 0.05
Prescribed medications 684 (370,998) 309 (198,421) 374 (32,717) 0.03
Emergency room 277 (186,367) 106 (99,114) 170 (78,261) 0.0002
Inpatient 1224 (289,2159) 455 (359,551) 768 (−182,1720) 0.112
Other 587 (451,722) 452 (425,480) 134 (−7,275) 0.062

Note: Expenditures adjusted for predisposing factors, enabling resources, and need factors covariates as specified in the Anderson behavioral model of medical use. CI=confidence interval. DGBI=Disorders of gut-brain interaction.

While expenditure for private insurance and out of pocket expenditures did not differ between pediatric DGBI patients and controls (Table 3), the incremental expenditure for Medicaid/CHIP was $1,926 (95% CI: $790-$3,063) higher for DGBI patients compared to controls.

Table 3.

Sources of adjusted mean annual estimated medical expenditures of pediatric patients with DGBI versus those without.

Pediatric DGBI (A)
$ (95% CI)
Controls (B)
$ (95% CI)
Incremental expenditures associated with pediatric DGBI (A-B)
$ (95% CI)
p-value
Private 1645 (1064, 2226) 1340 (1206,1474) 304 (−302, 912) 0.324
Medicaid/CHIP 2753 (1629,3877) 826 (701, 952) 1926 (790, 3063) 0.0009
Out of pocket 443 (296,591) 356 (332, 380) 87 (−62, 237) 0.25
Other combined 7 (0,194) 58 (38, 78) 38 (−59,137) 0.44

Note: Expenditures adjusted for predisposing factors, enabling resources, and need factors covariates as specified in the Anderson behavioral model of medical use. CI=confidence interval. DGBI=Disorders of gut-brain interaction.

National expenditures of pediatric DGBI

Our weighted estimated prevalence of children with DGBI was 805,931 per year. Multiplying this number by the coefficient of our OLS regression ($2,587) results in the national burden. The total annual expenditures associated with pediatric DGBI was $2.08 billion.

DISCUSSION

Key findings

We conducted the first nationally representative study examining comprehensive expenditures of the most common pediatric DGBI. Total per patient yearly medical expenditures in the United States was about $5,200 for pediatric patients with DGBI – an estimate that was over $2,500 more than the medical expenditures for medical seeking children without DGBI, even accounting for medical comorbidities and other predisposing and enabling factors. Incremental spending from DGBI patients versus patients without DGBI was highest for outpatient visits followed by office-based visits, prescribed medications, and emergency room visits. While private insurance and out of pocket expenditures did not differ for children with and without DGBI, Medicaid/CHIP contributed approximately $2,000 more to DGBI patients’ medical compared to controls. Strikingly, the national annual expenditures for pediatric patients with DGBI totaled over 2 billion dollars.

Findings in context of previous literature

Our medical expenditure estimates are generally consistent with existing literature that utilized samples that were not representative of the US population and only assessed expenditure of pediatric abdominal pain-associated DGBI. Specifically, a study of 122 4- to 21-year-old patients with an abdominal pain-associated DGBI (i.e., irritable bowel syndrome, functional dyspepsia, functional abdominal pain, abdominal migraine) reported the average expenditures per patient was $6,104 (range $1,052–$20,994).6 Similarly, a study of 932,592 8- to 18-year olds in the United States with private insurance reported that the mean annual all-cause incremental spending of members with irritable bowel syndrome was $6,364.60 in 2014 compared to controls when adjusting for age and gender.5 Our adjusted estimates of pediatric DGBI cost of $5,200 was similar, though slightly lower. The slightly higher estimates in prior research may have been due to these studies not accounting for differences in sociodemographic and health characteristics between patients with and without DGBI. Indeed, in our unadjusted analyses DGBI were associated with higher expenditure.

Our results showing variation in expenditures by service type are also consistent with previous studies showing that pediatric DGBI medical expenditure varies by provider type and medical system.12,13 Specifically, a study with 89 7- to 10-year-olds with irritable bowel syndrome in the United States found that cost of medical evaluation was fivefold higher for children evaluated by a gastroenterologist,12 and a study with 13,214 8- to 17-year-olds with abdominal pain-associated DGBI from 100 non-affiliated medical systems reported that expenditures varied considerably across systems.13

In terms of expenditures of inpatient care, we found that annual inpatient expenditures of DGBI totaled $1,224 per patient. A study of 22.3 million hospitalizations of 4- to 18-years-olds with primary discharge DGBI diagnoses (abdominal pain, constipation, irritable bowel syndrome, dyspepsia, abdominal migraine, cyclic vomiting syndrome, fecal incontinence) reported expenditures averaged $6,216 per admission.8 A study of 23,570 hospital admissions of patients up to the age of 18 years with a (1) primary diagnosis of fecal impaction or (2) a primary diagnosis of abdominal pain or constipation with a secondary diagnosis of fecal impaction reported per admission mean hospitalization charges increased over the study years, with charges totaling $15,234 in 2011 and $22,487 in 2019.9 It is not possible to directly compare our results to these study because we estimated expenditures per patient while these studies estimated expenditures only among admitted patients. Moreover, diagnoses included were also not the same. Specifically, the previous study that evaluated DGBI hospital admission expenditures8 included additional diagnoses we could not include (i.e., abdominal migraine, cyclic vomiting syndrome, fecal incontinence). The study that evaluated expenditures of hospital admissions due to fecal impaction9 did not limit the study to fecal impactions due to DGBI; therefore, we cannot draw conclusions about pediatric DGBI expenditures specifically from this study.

Study strengths and implications

Our study has several notable strengths that make it distinct from previous research. We utilized a large, nationally representative sample of pediatric patients and included the three most common pediatric DGBI conditions. Notably, the majority of previous studies did not include functional constipation – the most common DGBI.1 We were also able to examine service-specific expenditures because MEPS is the most comprehensive database for estimating medical expenditure. Finally, we adjusted for treatment enabling resources and co-morbid medical conditions to accurately estimate incremental expenditures associated with DGBI compared to controls.

Our study also has potential important real-world implications. Specifically, our findings suggest that effectively diagnosing and treating pediatric DGBI may have the potential to substantially reduce the annual medical expenditures. Early diagnoses and treatment of pediatric DGBI could also potentially prevent future healthcare expenditure given that that a large proportion of pediatric patients with DGBI historically have continued to experience symptoms into adulthood14 and have repeat diagnoses as adults.15 Given the lack of research to date to guide treatment for pediatric DGBI,16 rigorous, large-scale studies are critically needed to improve screening for pediatric DGBI, as well as evaluate the safety and effectiveness of pediatric DGBI treatments. Evidence generated from these studies must be widely disseminated across medical specialties to ensure broad screening and timely intervention. Improved screening and treatment practices have the potential to both alleviate suffering caused by pediatric DGBI and substantially reduce national medical expenditure.

Study limitations

It important to consider our findings in light of two study limitations. First, we did not estimate indirect expenditures, such as lost revenue from caregiver missing work. Second, because MEPS only provides 3-digit ICD-10 diagnostic codes rather than fully specified codes, we could not include less frequent diagnoses of abdominal migraines, functional nausea and vomiting, and nonretentive fecal incontinence, and we were not able to exclude neurogenic bowel and megacolon – not otherwise classified. However, it is important to note that we were able capture the three most common pediatric DGBI conditions and the prevalence of neurogenic bowel disease and megacolon – not otherwise classified in our sample is likely low given that conditions lead to neurogenic bowel disease (e.g., cerebral palsy, pediatric multiple sclerosis)17 and megacolon (e.g., Hirschsprung disease)18 are rare in the general pediatric population. Therefore, our results likely reflect conservative expenditure estimates.

CONCLUSION

This study extends prior literature by providing the most comprehensive expenditure estimates for pediatric DGBI in the United States. The results illuminate the significant national expenditure associated with pediatric DGBI, suggesting the potential importance of early detection and effective treatment for pediatric DGBI and the need for future research to improve screenings and evidence-based treatment for pediatric DGBI.

Supplementary Material

Goodness of fit testing showing smallest residuals (and therefore best fit) with an OLS adjusted regression model

Supplemental figure 1. Goodness of fit testing showing smallest residuals (and therefore best fit) with an OLS adjusted regression model.

KEY POINTS.

  • No prior studies have rigorously evaluated national medical expenditures associated with pediatric disorders of gut-brain interaction (DGBI), which are common and linked to reduced quality of life.

  • Using data from a large-scale, nationally representative survey of the U.S. population, we estimated individual- and national-level medical expenditures associated with common DGBI conditions among individuals ≤18 years.

  • Findings revealed substantial national medical expenditures associated with pediatric DGBI, suggesting that early diagnosis and effective, evidence-based treatment approaches may reduce the public health and economic burden of these conditions.

ACKNOWLEDGEMENTS

Research reported in publication was supported by the National Institute of General Medical Sciences and the National Institute of Arthritis and Musculoskeletal and Skin Diseases of the National Institutes of Health under award numbers T32GM089626 (ACS), K24AR080786 (JAR), and R01HL166337 (CBG). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Footnotes

Competing Interests: The authors have no competing interests.

REFERENCES

  • 1.Velasco-Benítez CA, Collazos-Saa LI, García-Perdomo HA. A systematic review and meta-analysis in schoolchildren and adolescents with functional gastrointestinal disorders according to Rome IV criteria. Arquivos de Gastroenterologia. 2022;59(2):304–313. [DOI] [PubMed] [Google Scholar]
  • 2.Palsson O, Simren M, Sperber AD, Bangdiwala S, Hreinsson JP, Aziz I. The Prevalence and Burden of Disorders of Gut-Brain Interaction (DGBI) Before vs After the COVID-19 Pandemic. Clinical Gastroenterology and Hepatology. doi: 10.1016/j.cgh.2025.07.012 [DOI] [PubMed] [Google Scholar]
  • 3.Tornkvist NT, Simrén M, Hreinsson JP, et al. Prevalence and impact of disorders of Gut-Brain interaction in Sweden. Neurogastroenterology and Motility. Jun 2023;35(6)doi: 10.1111/nmo.14578 [DOI] [PubMed] [Google Scholar]
  • 4.Sjölund J, Kull I, Bergström A, et al. Quality of Life and Bidirectional Gut-Brain Interactions in Irritable Bowel Syndrome From Adolescence to Adulthood. Clinical Gastroenterology and Hepatology. Apr 2024;22(4):858–866. doi: 10.1016/j.cgh.2023.09.022 [DOI] [PubMed] [Google Scholar]
  • 5.Beinvogl B, Palmer N, Kohane I, Nurko S. Healthcare spending and utilization for pediatric Irritable Bowel Syndrome in a commercially insured population. Neurogastroenterol Motil. Nov 2021;33(11):e14147. doi: 10.1111/nmo.14147 [DOI] [PubMed] [Google Scholar]
  • 6.Dhroove G, Chogle A, Saps M. A million-dollar work-up for abdominal pain: is it worth it? J Pediatr Gastroenterol Nutr. Nov 2010;51(5):579–83. doi: 10.1097/MPG.0b013e3181de0639 [DOI] [PubMed] [Google Scholar]
  • 7.Hoekman DR, Rutten JM, Vlieger AM, Benninga MA, Dijkgraaf MG. Annual Costs of Care for Pediatric Irritable Bowel Syndrome, Functional Abdominal Pain, and Functional Abdominal Pain Syndrome. J Pediatr. Nov 2015;167(5):1103–8.e2. doi: 10.1016/j.jpeds.2015.07.058 [DOI] [PubMed] [Google Scholar]
  • 8.Hollier JM, Salemi JL, Shulman RJ. United States Healthcare Burden of Pediatric Functional Gastrointestinal Pain Disorder Hospitalizations from 2002 to 2018. Neurogastroenterol Motil. Jul 2022;34(7):e14288. doi: 10.1111/nmo.14288 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Le D, Durrani H, Khatana J, Velayuthan S, Sankararaman S, Thavamani A. Hospitalization Trends and Healthcare Resource Utilization for Fecal Impactions in Pediatric Patients with Functional Constipation. J Clin Med. Jan 17 2025;14(2)doi: 10.3390/jcm14020569 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Agency for Healthcare Research and Quality (AHRQ). Using appropriate price indices for analyses of health care expenditure or income across multiple years. https://meps.ahrq.gov/about_meps/Price_Index.shtml
  • 11.Sun JW, Bourgeois FT, Haneuse S, et al. Development and Validation of a Pediatric Comorbidity Index. Am J Epidemiol. May 4 2021;190(5):918–927. doi: 10.1093/aje/kwaa244 [DOI] [PubMed] [Google Scholar]
  • 12.Lane MM, Weidler EM, Czyzewski DI, Shulman RJ. Pain symptoms and stooling patterns do not drive diagnostic costs for children with functional abdominal pain and irritable bowel syndrome in primary or tertiary care. Pediatrics. Mar 2009;123(3):758–64. doi: 10.1542/peds.2008-0227 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Livitz M, Friesen AS, Glynn EF, Schurman JV, Colombo JM, Friesen CA. Healthcare System-to-System Cost Variability in the Care of Pediatric Abdominal Pain-Associated Functional Gastrointestinal Disorders. Children (Basel). Nov 1 2021;8(11)doi: 10.3390/children8110985 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Walker LS, Dengler-Crish CM, Rippel S, Bruehl S. Functional abdominal pain in childhood and adolescence increases risk for chronic pain in adulthood. Pain. Sep 2010;150(3):568–572. doi: 10.1016/j.pain.2010.06.018 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Jones MP, Koloski NA, Walker MM, et al. A Minority of Childhood Disorders of Gut-Brain Interaction Persist Into Adulthood: A Risk-Factor Analysis. American Journal of Gastroenterology. Sep 2024;119(9):1894–1900. doi: 10.14309/ajg.0000000000002751 [DOI] [PubMed] [Google Scholar]
  • 16.Rexwinkel R, de Bruijn CMA, Gordon M, Benninga MA, Tabbers MM. Pharmacologic Treatment in Functional Abdominal Pain Disorders in Children: A Systematic Review. Pediatrics. Jun 2021;147(6)doi: 10.1542/peds.2020-042101 [DOI] [PubMed] [Google Scholar]
  • 17.Mosiello G, Safder S, Marshall D, Rolle U, Benninga MA. Neurogenic Bowel Dysfunction in Children and Adolescents. Journal of Clinical Medicine. 2021;10(8):1669. doi: 10.3390/jcm10081669 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Wang XJ, Camilleri M. Chronic Megacolon Presenting in Adolescents or Adults: Clinical Manifestations, Diagnosis, and Genetic Associations. Dig Dis Sci. Oct 2019;64(10):2750–2756. doi: 10.1007/s10620-019-05605-7 [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Goodness of fit testing showing smallest residuals (and therefore best fit) with an OLS adjusted regression model

Supplemental figure 1. Goodness of fit testing showing smallest residuals (and therefore best fit) with an OLS adjusted regression model.

RESOURCES