Risk factors for pulmonary function alterations in children with metabolic dysfunction-associated fatty liver disease

Abstract

Children with metabolic dysfunction-associated fatty liver disease (MAFLD) may exhibit abnormal lung function. However, it is unclear whether these abnormalities are independent of BMI. Moreover, the specific patterns of abnormal pulmonary function parameters have not been fully characterized, and the risk factors associated with impaired pulmonary function remain insufficiently understood. This study included 40 overweight or obese children with MAFLD and 30 overweight or obese control subjects without MAFLD. Pulmonary function parameters and anthropometric parameters were compared between children with MAFLD and the control group. Additionally, liver function, lipid and glucose metabolism, and cytokine levels were assessed. Multivariable regression analysis was used to identify risk factors for abnormal pulmonary function in children with MAFLD. No significant difference in BMI was observed between the groups (p = 0.075). Pulmonary function tests showed that FVC was significantly higher in children with MAFLD compared to controls (p < 0.001). In contrast, PEF, FEV1/FVC, FEF50, FEF75, and MMEF were lower in the MAFLD group (p < 0.05). Multivariable regression analysis demonstrated that HOMA-IR was significantly and inversely associated with FEF25 (b = -1.51, 95% CI: -2.33 to -0.69, p = 0.001), FEF50 (b = -1.85, 95% CI: -3.01 to -0.70, p = 0.003), and FEF75 (b = -1.44, 95% CI: -2.53 to -0.35, p = 0.01) among children with MAFLD. Furthermore, IL-1β levels were negatively correlated with MMEF (b = -1.16, 95% CI: -2.17 to -0.149, p = 0.03) and FEF50 (b = -0.63, 95% CI: -1.16 to -0.09, p = 0.02). These findings indicate that children aged 8 to 14 years with MAFLD exhibit higher FVC, along with a lower FEV1/FVC ratio and impaired small airway function compared to controls. This impairment in lung function is independent of BMI. Furthermore, HOMA-IR values and elevated IL-1β levels are key risk factors linked to abnormal small airway function.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-025-27313-1.

Introduction

Nonalcoholic fatty liver disease (NAFLD) is recognized as the primary etiology of chronic liver disease in young children¹. An international panel of liver disease experts argued that the diagnostic model for NAFLD placed excessive reliance on exclusion-based diagnosis. To better highlight the pathogenic role of metabolic dysfunction, they proposed renaming pediatric NAFLD as metabolic dysfunction-associated fatty liver disease (MAFLD) and adopting age-appropriate MAFLD definitions tailored to gender and age-specific percentiles. The diagnostic criteria for pediatric MAFLD include the confirmation of intrahepatic fat accumulation (steatosis) via liver histology (biopsy), imaging techniques, or blood biomarkers, in conjunction with at least one of the following conditions: excess adiposity, prediabetes or type 2 diabetes, or documented evidence of metabolic dysfunction². In 2024, a global consensus from various disciplines on pediatric metabolic dysfunction-associated fatty liver disease indicates that MAFLD might be linked to abnormal lung function tests, regardless of BMI³. However, this conclusion lacks sufficient evidence to support it. Multiple studies have indicated that MAFLD in adults is associated with impaired lung function^4–6. Studies have shown that if there is abnormal lung function during childhood, it can lead to lower lung function in young adulthood and old age compared to the same age group. Additionally, this increases the risk of developing chronic obstructive pulmonary disease (COPD) at an earlier stage and is closely associated with severe COPD in elderly individuals^7,8, There is a paucity of research examining the correlation between MAFLD and pulmonary function in pediatric populations, with only one study providing evidence that impaired lung function in children with MAFLD is independently associated with insulin resistance (IR) and high sensitive C reactive protein (hs-CRP) levels⁹. BMI is one of the key criteria for diagnosing MAFLD in children. However, it remains unclear whether lung function abnormalities in children with MAFLD are independent of BMI. This study aims to compare lung function differences between overweight or obese children without MAFLD and those diagnosed with MAFLD, while simultaneously analyzing potential risk factors to preliminarily elucidate the specific impact of MAFLD on pediatric lung function.

Materials and methods

Sample collection

The sample size was calculated using G*Power 3.1.9.7 software, with the main indicator being IR based on a previous study¹⁰, with effect-size = 0.8 α = 0.05 and power = 0.90. It is recommended to include at least 28 cases in each group to ensure robust results. In this study, we retrospectively analyzed the medical records of children who visited the outpatient department of our hospital between January 1, 2023, and December 31, 2024, and were diagnosed with obesity or overweight (BMI > + 1 SD defines overweight, and > + 2 SD defines obesity). Among these, 40 overweight or obese children with complete medical records who met the diagnostic criteria for MAFLD were included (17 girls and 23 boys). Additionally, 30 children diagnosed as overweight or obese but without fatty liver disease were also included (13 girls and 17 boys). The detailed data were accessed and collected for research purposes from August 26, 2024, to May 31, 2025. Given the retrospective nature of this study, following review by the ethics committee, the need for informed consent was waived by Anhui Public Health Clinical Center ethics committee. Nevertheless, all identifying information was securely stored and managed in accordance with strict confidentiality protocols to ensure the protection of participant privacy. The study was conducted in adherence to the principles outlined in the Declaration of Helsinki, and all methods were carried out in compliance with relevant guidelines and regulations. Ethical approval for this study was obtained from the Medical Ethics Committee of our institution [Approval ID: PJ-YX2024-041 (F1)].

Inclusion criteria

(1) Both genders, aged between 8 and 14 years, A comprehensive and accurate medical history was required. (2) The presence of at least two out of three abnormal findings on abdominal ultrasonography can be used to define fatty liver: (a) diffusely increased echogenicity in the liver with a greater echogenicity than the kidney or spleen. (b) vascular blurring. (c) deep attenuation of ultrasound signal¹¹. (3) BMI > 1 SD above the WHO growth reference median².

Exclusion criteria

(1) Patients with congenital heart disease, respiratory system disorders (especially asthma or allergic rhinitis), neuromuscular system disorders, immune system disorders, inherited metabolic diseases and other comorbidities. (2) Viral hepatitis, drug-induced hepatitis, alcoholic hepatitis and autoimmune liver disease. (3) Patients undergoing sex hormone therapy, growth hormone therapy or glucocorticoid therapy. (4) Children with a confirmed respiratory infection within the past one month. (5) Children diagnosed with asthma or having a family history of asthma. (6) Children with a history of liver surgery, heart surgery or lung surgery.

Clinical and laboratory evaluation

Clinical data and laboratory examination results for all enrolled children were collected via the electronic medical record system

The data included anthropometric measurements [height, weight, waist circumference (WC), body mass index (BMI)] and biochemical parameters [serum fasting blood glucose (FBG), fasting insulin (FINS), cholesterol (CHOL), triglyceride (TG), gamma-glutamyl transpeptidase (GGT), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), alanine aminotransferase (ALT), aspartate aminotransferase (AST) levels, as well as serum interleukin-1β (IL-1β) and interleukin-18 (IL-18)]. Biochemical parameters were quantitatively detected by ADVIA Chemistry XPT system (Siemens, Akishima, Tokyo, Japan). respectively. Insulin resistance index (HOMA-IR) was calculated using the formula: HOMA-IR = fasting insulin [µU/l]*fasting glucose [mmol/l]/22.5. The TyG index was calculated using a logarithmic formula: ln [fasting triglyceride (mg/dl) × fasting blood glucose (mg/dl)/2]. Serum levels of IL-1β and IL-18 were quantified using flow cytometry.

The techniques for assessing pulmonary function

The Cardiopulmonary function tester(Power Cube-ST, Kelord Co, Chongqing, China) was utilized to conduct tests in accordance with the standardized procedure prescribed by the guidelines of the American Thoracic Society¹². The measured parameters included forced vital capacity (FVC), forced expiratory volume in one second (FEV1), FEV1/FVC ratio, peak expiratory flow (PEF), and expiratory flow at 25%, 50%, and 75% of vital capacity (FEF25, FEF50, FEF75). Additionally, maximal mid-expiratory flow (MMEF) was also assessed. All measurement results were expressed as a percentage of the predicted value.

Statistical methods

IBM SPSS 26.0 software was utilized for data analysis. The Shapiro-Wilk test was employed to assess normality. Continuous variables conforming to a normal distribution were presented as mean ± SD. An independent samples t-test was used to compare the two groups. When variances are unequal, the Welch t-test is recommended for assessing mean differences between independent groups. Whereas variables with a skewed distribution were reported as median and interquartile range. To evaluate differences among groups, the non-parametric Mann-Whitney U test was employed. Categorical variables were summarized as frequency (percentage) [n (%)] and analyzed for group comparisons using the chi-square test. Spearman correlation analysis was performed to examine variable correlations, variables with a correlation coefficient |r| > 0.4 and p < 0.01 in univariate analysis were included in a multivariable regression model to identify independent risk factors. Multivariable regression analysis was employed to investigate factors influencing the pulmonary function index, with statistical significance set at p < 0.05. All within-cohort correlation/regression analyses were prespecified to be performed exclusively in the MAFLD subgroup (n = 40) to identify disease-specific determinants.

Results

Baseline demographic and laboratory data in the study groups

There were no significant differences in gender, age, weight, height, BMI and WC between the control group and the MAFLD group (p > 0.05). Moreover, levels of ALT, CHOL, FINS, HOMA-IR, IL-1β and IL-18 were significantly elevated in the MAFLD group compared to the control group (p < 0.001). Additionally, AST and LDL-C levels were significantly higher in the MAFLD group than in the control group (p < 0.05). (Table 1)

Table 1.

Baseline demographic and laboratory data in the study groups.

Variables	Control group (n = 30)	MAFLD group (n = 40)	χ2/t/z	p
Gender			0.005	0.944
Boy	17(56.70)	23(57.50)
Girl	13(43.30)	17(42.50)
Age(year)	11.18 ± 1.51	11.14 ± 1.62	0.112	0.911
Weight(kg)	57[52,62.5]	55[48.5,62.75]	−0.244	0.808
Height(cm)	150.6 ± 10.2	147.73 ± 12.08	1.052	0.297
BMI(kg/m2)	24.54[23.69,25.81]	25.08[24.5,27.05]	−1.780	0.075
WC(cm)	74.33 ± 3.73	76.36 ± 5	−1.864	0.067
ALT(IU/L)	17[12,27]	40[19.5,52.5]	−4.322	< 0.001***
AST(IU/L)	20[12,24]	25.5[18,50]	−2.993	0.003*
GGT(IU/L)	18[15,21]	15[12,18.5]	−1.826	0.068
CHOL (mmol/L)	4.48 ± 0.62	5.1 ± 0.85	−3.517	< 0.001***
TG(mmol/L)	1.1 ± 0.35	1.2 ± 0.46	−1.053	0.296
HDL-C(mmol/L)	1.74 ± 0.29	1.75 ± 0.4	−0.027	0.979
LDL-C(mmol/L)	1.9 ± 0.58	2.42 ± 0.87	−2.995	0.004*
FBG(mmol/L)	4.96 ± 0.6	5.18 ± 0.54	−1.563	0.123
FINS(pmol/L)	84.73 ± 28.57	129.83 ± 42.77	−5.28	< 0.001***
HOMA-IR	2.57[1.78,3.31]	4.06[2.97,5.57]	−4.13	< 0.001***
TyG	8.31 ± 0.43	8.42 ± 0.48	−1.001	0.320
IL-1β(pg/mL)	10.96 ± 3.82	20.11 ± 6.67	−7.237	< 0.001***
IL-18(pg/mL)	55.04[35.2,73.62]	75.1[58.41,98.75]	−3.365	< 0.001***

***p < 0.001, *p < 0.05. The chi-square test was employed to compare gender differences. The Mann–Whitney U test was applied for variables that were not normally distributed, including Weight, BMI, ALT, AST, GGT, HOMA-IR, and IL-18. The Welch’s t-test was utilized for the comparison of TC, LDL-C, FINS, and IL-1β, which exhibited heterogeneous variances. The student’s t-test was used to analyze normally distributed continuous variables such as Height, WC, TG, HDL-C, FBG. BMI: Body mass index, WC: waist circumference, ALT: alanine aminotransferase, AST: aspartate aminotransferase, GGT: γ-glutamyl transpeptidase, CHOL: cholesterol, TG: triglyceride, HDL-C: high-density lipoprotein cholesterol, LDL-C: low-density lipoprotein cholesterol, FBG: fasting blood glucose, FINS fasting insulin, HOMA-IR: Insulin resistance index, TyG: the triglyceride-glucose index, IL-1β: interleukin-1β, IL-18: interleukin-18.

Pulmonary function test data in the enrolled children

The FVC values were significantly higher in the MAFLD group than in the control group (p < 0.001). FEV1/FVC, PEF, FEF50, FEF75, and MMEF were significantly lower in the MAFLD group (p < 0.05). (Table 2)

Table 2.

Pulmonary function test data in the enrolled children.

Variables	Control group (n = 30)	MAFLD group (n = 40)	t/z	p
FVC	94.37 ± 3.49	98.3 ± 2.8	−5.23	< 0.001***
FEV1	91.1 ± 4.77	91.15 ± 4.2	−0.047	0.963
FEV1/FVC	96.72[94.44,98.84]	92.78[90.86,94.03]	−4.238	< 0.001***
PEF	93.63 ± 3.73	86.55 ± 5.03	6.485	< 0.001***
FEF25	86.3 ± 6	85.03 ± 5.12	0.958	0.341
FEF50	80.5 ± 4.81	77.4 ± 5.9	2.352	0.022*
FEF75	75.17 ± 5.19	71.63 ± 5.02	2.879	0.005*
MMEF	78.37 ± 5.32	72.58 ± 7.09	3.904	< 0.001***

***p < 0.001, *p < 0.05, The Mann–Whitney U test was applied for variables that were not normally distributed, including FEV1/FVC. The Welch’s t-test was utilized for the comparison of MMEF, which exhibited heterogeneous variances. The student’ s t-test was used to analyze normally distributed continuous variables such as FVC, PEF, FEF25, FEF50, and FEF75. FVC: forced vital capacity, FEV1:forced expiratory volume in one second, PEF: peak expiratory flow, FEF25, FEF50, FEF75: expiratory flow at 25%, 50% and 75% of vital capacity, MMEF: maximal mid-expiratory flow.

Spearman correlation analysis and multivariable regression analysis results between pulmonary function variables and clinical variables in children with MAFLD

Spearman correlation analysis revealed significant associations between pulmonary function parameters and various biochemical, metabolic, and inflammatory indicators in children with MAFLD (Table 3). Variables with a correlation coefficient |r| > 0.4 and p < 0.01 in univariate analysis were included in a multivariable regression analysis model to identify independent risk factors. Multivariable regression analysis did not reveal any statistically significant risk factors associated with FEF, FEV1, or FEV1/FVC (Tables 4, 5 and 6). Multivariable regression analysis demonstrated that HOMA-IR was significantly and inversely associated with FEF25 (b = −1.51, 95% CI: −2.33 to −0.69, p = 0.001), FEF50 (b = −1.85, 95% CI: −3.01 to −0.70, p = 0.003), and FEF75 (b = −1.44, 95% CI: −2.53 to −0.35, p = 0.01) among children with MAFLD (Tables 7 and 8, and 9). Specifically, each 1-unit increase in HOMA-IR was linked to a 1.51% reduction in FEF25, a 1.85% reduction in FEF50, and a 1.44% reduction in FEF75. Furthermore, IL-1β levels were negatively correlated with MMEF (b = −1.16, 95% CI: −2.17 to −0.149, p = 0.03) and FEF50 (b = −0.63, 95% CI: −1.16 to −0.09, p = 0.02), such that each 1 pg/mL rise in IL-1β corresponded to a 1.16% decline in MMEF and a 0.63% decline in FEF50 (Tables 8 and 10).

Table 3.

Spearman correlation analysis results between pulmonary function variables and clinical variables in children with MAFLD.

Variables	FVC	FEV1	PEF	FEV1/FVC	FEF 25	FEF 50	FEF 75	MMEF
Gender	0.331*	0.174	0.092	−0.066	0.015	0.119	0.079	0.059
Age(year)	−0.191	−0.355*	−0.183	− 0.353*	−0.246	−0.109	−0.157	−0.071
BMI(kg/m2)	0.159	0–0.043.043	0.122	−0.161	−0.129	−0.331*	−0.295	−0.398*
WC(cm)	−0.204	−0.373*	−0.187	− 0.359*	−0.307	−0.147	−0.168	−0.065
ALT(IU/L)	0.102	−0.174	−0.307	−0.257	−0.381*	−0.605**	−0.578**	−0.653**
AST(IU/L)	−0.152	−0.293	−0.166	−0.174	−0.219	−0.371*	−0.344*	−0.558**
GGT(IU/L)	0.173	0.25	0.081	0.276	0.071	0.064	0.045	0.142
CHOL (mmol/L)	−0.131	−0.388*	−0.122	− 0.320*	−0.281	−0.548**	−0.512**	−0.616**
TG(mmol/L)	−0.206	−0.51**	−0.431**	− 0.508**	−0.370*	−0.374*	−0.372*	−0.517**
HDL-C(mmol/L)	−0.019	0.262	0.229	0.27	0.251	0.350*	0.296	0.393*
LDL-C(mmol/L)	0.276	0.05	−0.235	−0.094	−0.137	−0.515**	−0.494**	−0.610**
HOMA-IR	−0.131	−0.460**	−0.326*	−0.443**	− 0.574**	−0.675**	−0.685**	−0.564**
TyG	−0.203	−0.517**	−0.412**	−0.504**	−0.387*	−0.436**	−0.433**	−0.573**
IL-1β(pg/mL)	0.164	−0.068	−0.332*	−0.194	−0.345*	−0.606**	−0.573**	−0.623**
IL-18(pg/mL)	0.195	0.023	−0.281	−0.078	−0.203	−0.472**	−0.447**	−0.515**

**p < 0.01, *p < 0.05, For detailed information regarding r values and p values, please refer to Supplementary Material 1. BMI: Body mass index, WC: waist circumference, ALT: alanine aminotransferase, AST: aspartate aminotransferase, GGT: γ-glutamyl transpeptidase, CHOL: cholesterol, TG: triglyceride, HDL-C: high-density lipoprotein cholesterol, LDL-C: low-density lipoprotein cholesterol, HOMA-IR: Insulin resistance index, IL-1β: interleukin-1β, IL-18: interleukin-18.

Table 4.

Multivariable regression analysis of the MAFLD cohort showed factors associated with FEV1.

Variables	b-value	b-value SE	t	p	95% CI
TG(mmol/L)	−2.38	−0.26	−0.45	0.66	−13.20	8.43
TyG	−0.14	−0.02	−0.03	0.98	−10.84	10.56
HOMA-IR	−0.59	−0.25	−1.23	0.23	−1.56	0.38

TG: triglyceride, TyG: Triglyceride-glucose index, HOMA-IR: Insulin resistance index, FEV1: forced expiratory volume in one second,.

Table 5.

Multivariable regression analysis of the MAFLD cohort showed factors associated with PEF.

Variables	b-value	b-value SE	t	p	95% CI
TG(mmol/L)	−2.30	−0.21	−0.35	0.73	−15.63	11.03
TyG	−1.82	−0.18	−0.29	0.77	−14.45	10.81

TG: triglyceride, TyG: Triglyceride-glucose index, PEF: peak expiratory flow.

Table 6.

Multivariable regression analysis of the MAFLD cohort showed factors associated with FEV 1/FVC.

Variables	b-value	b-value SE	t	p	95% CI
TG(mmol/L)	−3.87	−0.55	−0.97	0.34	−11.98	4.23
TyG	2.15	0.33	0.54	0.59	−5.87	10.17
HOMA-IR	−0.60	−0.33	−1.68	0.10	−1.33	0.12

TG: triglyceride, TyG: Triglyceride-glucose index, HOMA-IR: Insulin resistance index, FVC: forced vital capacity, FEV1: forced expiratory volume in one second.

Table 7.

Multivariable regression analysis of the MAFLD cohort showed factors associated with FEF25.

Variables	b-value	b-value SE	t	p	95% CI
HOMA-IR	−1.51	−0.52	−3.74	0.001	−2.33	−0.69

HOMA-IR: Insulin resistance index, FEF25: expiratory flow at 25% of vital capacity.

Table 8.

Multivariable regression analysis of the MAFLD cohort showed factors associated with FEF50.

Variables	b-value	b-value SE	t	p	95% CI
ALT(IU/L)	0.15	0.71	2.60	0.01	0.03	0.27
CHOL(mmol/L)	−1.05	−0.15	−0.99	0.33	−3.21	1.11
LDL-C(mmol/L)	−0.64	−0.09	−0.53	0.60	−3.10	1.82
HOMA-IR	−1.85	−0.55	−3.26	0.003	−3.01	−0.70
IL-1β(pg/mL)	−0.63	−0.71	−2.37	0.02	−1.16	−0.09

ALT: alanine aminotransferase, AST: aspartate aminotransferase, CHOL: cholesterol, LDL-C: low-density lipoprotein cholesterol, HOMA-IR: Insulin resistance index, IL-1β: interleukin-1β, FEF50: expiratory flow at 50% of vital capacity.

Table 9.

Multivariable regression analysis of the MAFLD cohort showed factors associated with FEF75.

Variables	b-value	b-value SE	t	p	95% CI
ALT(IU/L)	0.05	0.30	0.95	0.35	−0.06	0.17
CHOL(mmol/L)	−0.17	−0.03	−0.17	0.87	−2.27	1.93
LDL-C(mmol/L)	−0.64	−0.11	−0.59	0.56	−2.86	1.57
HOMA-IR	−1.44	−0.50	−2.68	0.01	−2.53	−0.35
IL-1β(pg/mL)	−0.73	−0.96	−1.94	0.06	−1.49	0.04
IL-18(pg/mL)	0.11	0.59	1.35	0.19	−0.06	0.27

ALT: alanine aminotransferase, CHOL: cholesterol, LDL-C: low-density lipoprotein cholesterol, HOMA-IR: Insulin resistance index, IL-1β: interleukin-1β, IL-18: interleukin-18, FEF75: expiratory flow at 75% of vital capacity,.

Table 10.

Multivariable regression analysis of the MAFLD cohort showed factors associated with MMEF.

Variables	b-value	b-value SE	t	p	95% CI
ALT(IU/L)	0.03	0.13	0.36	0.72	−0.16	0.23
AST(IU/L)	−0.10	−0.33	−1.45	0.16	−0.23	0.04
CHOL(mmol/L)	−0.37	−0.04	−0.25	0.80	−3.35	2.61
TG(mmol/L)	0.12	0.01	0.02	0.99	−14.81	15.06
LDL-C(mmol/L)	−1.93	−0.24	−1.33	0.19	−4.88	1.02
HOMA-IR	−0.76	−0.19	−0.90	0.38	−2.47	0.96
TyG	−1.28	−0.09	−0.18	0.86	−15.70	13.13
IL-1β(pg/mL)	−1.16	−1.09	−2.34	0.03	−2.17	−0.15
IL-18(pg/mL)	0.26	0.98	2.32	0.03	0.03	0.48

ALT: alanine aminotransferase, AST: aspartate aminotransferase, CHOL: cholesterol, TG: triglyceride, HDL-C: high-density lipoprotein cholesterol, HOMA-IR: Insulin resistance index, TyG: Triglyceride-glucose index, IL-1β: interleukin-1β, IL-18: interleukin-18, MMEF: maximal mid-expiratory flow.

Discussion

Among the complications associated with childhood obesity, MAFLD has garnered significant attention and is considered the primary etiology of chronic liver disease in children¹³. This study enrolled forty children aged 8–14 years with MAFLD. The levels of ALT, AST, CHOL, LDL-C, FINS, and HOMA-IR were found to be elevated compared to those in the control group, which aligns with the clinical characteristics of MAFLD accompanied by abnormal liver function as well as glucose and lipid metabolism disorders^14,15.

This study revealed that the FVC in the MAFLD group was significantly higher than that in the control group (97.23 ± 4.27 vs. 94.37 ± 3.49, t = 2.927, p = 0.005), whereas the FEV1/FVC ratio in the MAFLD group was significantly lower than that in the control group (94.14 ± 2.75 vs. 97.53 ± 3.05, p < 0.001). The data from this study indicated no statistically significant difference in BMI between the MAFLD group and the control group. Similarly, Multivariable regression analysis failed to reveal any significant correlation between FVC and BMI. Some studies have reported a decrease in FEV1, FVC, and FEV1/FVC with weight gain^16,17, while others have found a positive correlation between BMI and both FVC and FEV1, along with a negative correlation with the FEV1/FVC ratio^18–20. It is plausible that the rapid increase in BMI during childhood and adolescence affects lung volume more than it does airway growth, this variation could lead to a physiological disparity between the growth of lung parenchyma and the caliber of the airways²¹. A study conducted among 8-year-old children found no significant association between BMI and FEV1 or FVC²². These findings are consistent with the results of the present study, which demonstrates that lung function impairment in children with MAFLD occurs independently of BMI. These studies suggest that the influence of BMI on FVC and FEV1/FVC remains uncertain. A study indicates that this condition may be associated with decreased lung compliance in children with MAFLD. To preserve ventilatory efficiency, these individuals employ a deep inspiration strategy to enhance lung volume, thereby improving FVC²³. This study revealed that the FEV1/FVC ratio in the MAFLD group was significantly lower compared to the control group, suggesting that children with MAFLD may display early indicators of obstructive ventilatory dysfunction. However, it is important to note that part of this reduction in the ratio could be influenced by an increase in FVC, which may affect the interpretation of airflow limitation. Although MAFLD is frequently associated with obesity, not all individuals with obesity develop this condition. Moreover, a considerable proportion of MAFLD cases occur in individuals with a normal BMI, a phenotype known as lean MAFLD^24,25. This phenotype further underscores the uncertainty surrounding the association between BMI and the development and progression of MAFLD, supporting the central argument of this study—that impaired pulmonary function in children with MAFLD occurs independently of BMI.

This study demonstrates that the TyG index exhibits a strong correlation with FEV1, PEF, FEV1/FVC, FEF 50, FEF 75, and MMEF. Although Multivariable regression analysis did not reveal a stronger correlation between the TyG index and lung function parameters, Multivariable regression analysis indicated that different HOMA-IR values had significantly and inversely onFEF25, FEF 50 and FEF 75. The data from this study demonstrated a significant increase in HOMA-IR levels among the MAFLD group compared to the control group. Additionally, the MAFLD group exhibited significantly lower PEF values than the control group. Studies have observed a significant decrease in FVC among children with in IR¹⁶. The triglyceride-glucose index (TyG) is now widely acknowledged as a more accurate indicator of IR. Studies have shown that the TyG index is significantly inversely correlated with multiple pulmonary function parameters, such as FVC, FEV1/FVC and FEF75^26,27. These research results are consistent with the findings of this study. Given that the TyG index incorporates two parameters (triglycerides and blood glucose) while the primary components of HOMA-IR are blood glucose and insulin, this differential result suggests that the impact of childhood MAFLD on blood glucose and insulin is more pronounced than its effect on triglycerides. Animal studies have shown that the lack of insulin receptors in adipose tissue causes hepatic steatosis in mice²⁸, indicating that IR plays an essential role in the development of MAFLD. Since IR hinders glucose utilization and disturbs lipid metabolism, resulting in decreased ATP production and muscle weakness, it can ultimately affect lung function during forced respiration as assessed by spirometry in patients with MAFLD²⁹. PEF serves as a crucial indicator of airway patency and respiratory muscle strength, while FEF50 and FEF75 are important markers of small airway function³⁰. The findings suggest a potential association between IR and abnormal lung function in children with MAFLD, highlighting IR as a contributing factor to the decline of small airway function in this population. Current clinical evidence supports the use of metformin to improve insulin sensitivity in pediatric patients with MAFLD aged 10 years and older who demonstrate IR³¹. Accordingly, metformin is recommended as a therapeutic option for this specific subgroup of pediatric individuals with MAFLD.

In this study, a significant increase in IL-1β levels was observed in the MAFLD group compared to the control group (p < 0.001). Regression analysis demonstrated statistically significant associations between varying IL-1β levels and reduced FEF50 and MMEF values among children with MAFLD (b = −0.63, 95% CI: −1.16 to −0.09, p = 0.02; b = −1.16, 95% CI: −2.17 to −0.149, p = 0.03). This is the first instance where a correlation between IL-1β levels and small airway dysfunction has been identified. The IL-1 signaling pathway plays a pivotal role in regulating inflammation and immune response. The presence of inflammation is considered a key characteristic in the progression of MAFLD, leading to the transition from simple fat accumulation (steatosis) to non-alcoholic steatohepatitis³². Pathways involved in the activation of IL-1 family cytokines play a crucial role in the development and progression of MAFLD³³. In our previous study, we observed that in a mouse model of fatty liver disease induced by a high-fat, high-carbohydrate diet, IL-1β levels were significantly elevated in both serum and hepatic tissues, accompanied by increased NLRP3 expression and caspase-1 activation³⁴. Recently, the NLRP3 inflammasome has garnered significant attention in diseases associated with oxidative stress and inflammation, such as MAFLD^35,36. The NLRP3 inflammasome forms aggregates and becomes activated in response to pathogen-associated and damage-associated molecular patterns³⁷. Upon activation of the NLRP3 inflammasome, pro-caspase-1 undergoes cleavage to form activated caspase-1, which facilitates the maturation and secretion of IL-1β. Subsequently, IL-1β interacts with its receptor IL-1R1 to initiate immune cell activation and inflammatory responses. The recent discovery has demonstrated that Rilabnacept effectively inhibits inflammatory responses by sequestering IL-1β³⁸. We hypothesize that inhibiting the IL-1 signaling pathway may potentially alleviate liver and lung inflammation in pediatric patients diagnosed with MAFLD. However, it remains unclear whether IL-1β directly contributes to abnormal lung function in children with MAFLD. Further animal studies are required to assess airway mucosal inflammation in obese young mice with MAFLD, while simultaneously measuring levels of IL-1β and associated inflammatory markers in lung tissue or bronchoalveolar lavage fluid. Such investigations will provide insights into the role of these factors in the pathophysiological process underlying small airway dysfunction observed in children with MAFLD.

Conclusion

This study innovatively revealed that children aged 8 to 14 years with MAFLD exhibited significantly decreased lung function compared to overweight or obese children without MAFLD. Furthermore, this lung function impairment is independent of BMI. Additionally, IL-1β and IR may serve as critical risk factors contributing to small airway dysfunction in children with MAFLD.

The present study has some limitations. The participants were aged 8 to 14 and recruited from a single center in China, without stratification by gender or region, subgroup analyses according to different BMI categories were not conducted, the findings may lack generalizability to younger children or older adolescents with MAFLD. Future studies should use larger, more diverse samples across multiple centers to confirm these results. Well-designed animal studies are also needed to determine whether similar inflammatory changes occur in the lung microenvironment. Continuous pulmonary function tests have not been conducted on children with MAFLD. Consequently, it remains unclear whether interventions and improvements can reverse the pulmonary function abnormalities in these children.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contributions

S.-M.X: Conceptualization, Data curation, Methodology, Investigation, Writing-original draft, Funding acquisition. S.-Q.W: Conceptualization, Supervision, Validation, Writing-review & editing. Y.X: Data curation, Methodology, Investigation, Project administration. L.H: Methodology. L.-Q.Y: Formal Analysis, Supervision, Writing-review & editing.

Funding

This research was funded by Anhui Medical University Scientific Research Fund Project (No.2021xkj179).

Data availability

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.

Declarations

Competing interests

The authors declare no competing interests.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Ethics statement

The present study was granted approval by the Medical Ethics Committee of our hospital [Approval ID: PJ-YX2024-041 (F1)].