Gestational diabetes mellitus (GDM) is known to be associated with certain respiratory impairments in offspring. However, the specific association between maternal GDM and childhood lung function remains unclear. We examined the association of maternal glycemia, as measured by oral glucose tolerance test (OGTT) values, with childhood lung function outcomes in a birth cohort.
A follow-up study was conducted with 889 children aged 6 years whose mothers underwent a 75-g OGTT between 24 and 28 weeks of gestation. After adjusting for prenatal and postnatal factors, multivariable regression models were used to evaluate the relationship between maternal glycemia and offspring lung function.
In total, 10.7% of the offspring were exposed to maternal GDM. Maternal GDM significantly reduced the z score of forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), and forced expiratory flow at 25–75% of FVC in children, with more pronounced effects in female offspring. Maternal 1- and 2-h post-OGTT glucose z scores and the sum of those z scores, but not those for fasting glucose, were inversely associated with several measures of children's lung function. Additionally, maternal GDM increased the risk of impaired lung function in children (odds ratio 2.64; 95% CI, 1.10–5.85), defined as an FVC <85% of the predicted value. There were no significant associations with FEV1/FVC.
Maternal hyperglycemia was negatively associated with lung function in children, particularly among girls. Further studies are warranted to elucidate the underlying mechanisms of this association and to explore potential interventions to mitigate its effects.
Introduction
Gestational diabetes mellitus (GDM) is the most common metabolic issue during pregnancy, becoming more prevalent as obesity rates climb and mothers give birth at older ages (1). This condition does not just affect the health of mothers and their babies during pregnancy, it also has lasting effects that can affect a child's health into adulthood (2). Emerging evidence increasingly suggests that GDM plays a critical role in fetal pulmonary complications, such as hypoplasia, delayed lung maturation, and respiratory distress syndrome (3,4). Moreover, GDM may increase the risk of asthma and chronic lung diseases later in life (5–7). Despite these associations, no studies, to our knowledge, have yet examined the impact of maternal GDM on offspring lung function at 6 years—a key indicator of respiratory health and an important predictor of overall health, longevity, and quality of life.
Lung function development begins early in gestation and extends into early adulthood (8). Previous studies have indicated that abnormal lung function development not only increases the risk of pulmonary diseases in childhood but also contributes to various respiratory diseases in later life (9). Notably, recent research has emphasized the profound impact of maternal perinatal BMI and neonatal birth weight on early lung function development in children (5). Therefore, exploring the long-term respiratory health impacts of maternal GDM is crucial both for deepening our understanding of perinatal factors on respiratory health and for evaluating the potential consequences of maternal hyperglycemia on respiratory outcomes.
The aim of this study was to investigate the association between prenatal GDM exposure and lung function in 6-year-old children, using a longitudinal birth-cohort study. By incorporating various prenatal and postnatal environmental factors, our findings may provide novel insights into the intergenerational effects of GDM on respiratory health.
Research Design and Methods
Study Design and Participants
This study was part of an ongoing, prospective birth-cohort study conducted in Wuhan, China, from September 2012 to October 2019; comprehensive details on that study are provided elsewhere (10). The cohort included pregnant women who resided in the study city and delivered a healthy, single, live infant without any birth defects. All participants were ethnically Chinese. Participants with preexisting type 1 or type 2 diabetes were excluded based on medical history and early pregnancy screening. No additional screening was conducted prior to 24 weeks of gestation. Eligible participants underwent universal screening for GDM by undergoing a 75-g oral glucose tolerance test (OGTT) between 24 and 28 weeks of gestation, during which fasting, 1-h, and 2-h plasma glucose levels were recorded.
From May 2022 to August 2023, a follow-up study was carried out to assess the impact of prenatal GDM exposure on the lung function of children. During this period, children around 6 years of age underwent physical examinations at the Wuhan Maternal and Child Healthcare Hospital. A total of 1012 healthy children who successfully completed the lung function test were included in the present study. Of these, the final analysis focused on 889 children with available data on maternal OGTT results and corresponding lung function measurements (Fig. S1). Demographic characteristics of mothers and children were collected through face-to-face questionnaires. Though maternal lung function was not assessed, none of the participating women reported having chronic respiratory diseases. The research protocol was approved by the ethics committees of Tongji Medical College, Huazhong University of Science and Technology, and Wuhan Women and Children Medical and Healthcare Center.
Pulmonary Function Measurement (Spirometry)
Lung function assessments were conducted using a Jaeger MasterScreen Spirometer (Jaeger-Toennies GmbH). The assessments included forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), the FEV1 to FVC (FEV1/FVC) ratio, and forced expiratory flow at 25–75% of the pulmonary volume (FEF25-75%). FEV1 measures the amount of air a person can forcefully exhale in 1 s, which is a key indicator of pulmonary function. FVC represents the total volume of air exhaled after a full inhalation, and the FEV1/FVC ratio is used to diagnose obstructive and restrictive airway conditions. FEF25-75% assesses the speed of airflow in the middle portion of the exhalation and is sensitive to changes in the smaller airways. Adhering to the guidelines established by the American Thoracic Society (ATS) and the European Respiratory Society (ERS) for conducting lung function tests, these measures were designed to capture accurate lung function metrics (11).
During testing, participants stood wearing a nose clip to prevent nasal airflow and received detailed instructions on the procedure (12,13). A minimum of three spirometry tests were conducted per participant, selecting only those results meeting ATS/ERS criteria for proper initiation and consistency in FVC, with variations of <5% or <150 mL between the two highest values. Results were initially evaluated by a certified respiratory technician and then read by a pulmonologist to ensure data accuracy and reliability.
All child participants were screened for respiratory symptoms prior to testing, with symptomatic individuals rescheduled. Additionally, participants were instructed to refrain from asthma medications for at least 12 h before testing to ensure unbiased results. Lung function measurements were converted into z scores with adjustment for age, sex, height, and ethnicity, following the Global Lung Function Initiative (14). Decreased lung function was defined as either FEV1 or FVC <85% of the predicted value for these parameters (15). The two outcomes were evaluated in a binary manner, categorized as either decreased or normal, with each outcome variable analyzed independently.
Predictors
The primary predictors included GDM status and maternal glycemia, as determined by OGTT values, including fasting and 1- and 2-h glucose levels, each normalized by their SDs and the sum of their z scores (16). The diagnosis of GDM adhered to the guidelines established by the International Association of Diabetes and Pregnancy Study Groups (IADPSG) (17). An integrated measure of maternal glucose was derived from the sum of individual glucose z scores, which were calculated by subtracting the mean glucose level at each time point, dividing by the SD, and then summing these individual z scores.
Covariates
Maternal variables, including age, prepregnancy BMI, gestational week, educational attainment (≤9/10–12, 13–15, of≥16 schooling years), smoking status (yes or no), multiparity (yes or no), mode of delivery (vaginal delivery or cesarean delivery) and gravidity (1, 2, or ≥2), were obtained through a comprehensive questionnaire. Smoking was defined as either a mother who smoked at least one cigarette daily for >6 months before and during pregnancy or a nonsmoking woman who was exposed to cigarette smoke for at least 10 min each day during pregnancy. Child height was measured twice without shoes, using a stadiometer, and rounded to the nearest 0.5 cm; a reevaluation was conducted if discrepancies exceeded 1.0 cm Weight was measured twice to the nearest 0.1 kg, with a repeated assessment if variations exceeded 0.5 kg. Age-specific BMI z scores were calculated following the growth reference standards established by the World Health Organization (18). Data on children's age, sex (boys, girls), duration of breastfeeding (not applicable, ≥6, or <6 months), and respiratory diseases (yes or no) were collected through a questionnaire. Respiratory diseases were defined as any bronchiolitis, asthmatic bronchitis, asthmatic pneumonia, and bronchial asthma. Birth weight was extracted from electronic health records. The fasting plasma glucose levels of children, typically measured after a fasting period of 8–10 h, were determined using the hexokinase method.
Statistical Analysis
Frequencies and descriptive statistics were used to summarize the baseline characteristics of the participants, differentiated by offspring sex. Data are presented mean ± SD for continuous variables with normal distributions. Multiple linear regression was used to evaluate associations between maternal glucose predictors and continuous lung function outcomes. For dichotomous impaired lung function, multiple logistic regression was used. Covariate adjustments proceeded as follows: model 1 adjusted for child's age, sex, BMI z score, duration of breastfeeding, and respiratory diseases. Model 2 incorporated all variables from model 1 and further adjusted for maternal characteristics during pregnancy, such as age, education, gestational age, prepregnancy BMI, gestational weight gain, parity, gravidity, mode of delivery, and smoking habits. Model 3 expanded upon model 2 by additionally adjusting for the child's birth weight. Given prior evidence (19) and our findings linking children's glucose levels with lung function (Table S1), model 4 was developed by further incorporating child’s blood glucose levels into the model 3.
We used restricted cubic splines to investigate the dose-response relationship between OGTT values (fasting, 1-h, and 2-h) and lung function indicators. Three knots were set at the 10th (reference), 50th, and 90th percentiles of OGTT values to capture potential nonlinear relationships. Upon detecting nonlinearity, the turning point was initially identified, followed piece-wise linear regression to construct the model for both segments around this turning point. Subgroup analyses were conducted to assess variations within categories of sex and respiratory diseases. Tests for effect modification by subgroup were based on interaction terms between subgroup indicators.
To evaluate the shapes of maternal glucose values throughout the OGTT, group-based trajectory modeling was used to estimate trajectories of fasting, 1-h, and 2-h maternal glucose levels and to identify groups of mothers with similar OGTT trajectories according to latent class analysis. Model selection procedures for group-based trajectory modeling followed established recommendations from earlier studies (20). The optimal group model was chosen based on several criteria, including a minimum average group posterior probability value of 0.7, odds of correct classification based on posterior probabilities of group membership >5, practical and efficient model performance, adequate sample sizes in each group, and reasonably narrow CIs.
All data were analyzed using R, version 4.1.0. Statistical significance was determined by two-sided P < 0.05.
Results
Characteristics of the Study Population
Characteristics of the participating children and their mothers are summarized in Table 1. The average age of the mothers was 29.1 years, with a GDM prevalence of 10.7%. The children were followed up at an average age of 5.9 years. Analysis by sex revealed no significant differences in breastfeeding duration between boys and girls. However, boys had a higher incidence of respiratory diseases and slightly higher levels of FEV1 and FEV1/FVC z scores. Conversely, girls had better FEF25-75%z score values and marginally lower birth weights.
Characteristics of mothers during pregnancy and their children at follow-up, stratifying by offspring sex
Characteristic . | All (N = 889) . | Boys (n = 459) . | Girls (n = 430) . | P valuea . |
---|---|---|---|---|
Maternal | ||||
Age (years) | 29.1 ± 3.6 | 29.3 ± 3.7 | 29.0 ± 3.6 | 0.223 |
Gestational age (weeks) | 39.3 ± 1.2 | 39.2 ± 1.1 | 39.3 ± 1.2 | 0.269 |
Prepregnancy BMI (kg/m2) | 21.0 ± 2.9 | 21.2 ± 2.9 | 20.9 ± 2.8 | 0.094 |
Gestational weight gain (kg) | 16.1 ± 4.7 | 16.0 ± 4.7 | 16.2 ± 4.7 | 0.552 |
Education level (schooling years) | 0.414 | |||
≤9 | 47 (5.3) | 28 (6.1) | 19 (4.4) | |
10–12 | 186 (20.9) | 102 (22.2) | 84 (19.5) | |
13–15 | 598 (67.3) | 302 (65.8) | 296 (68.8) | |
≥16 | 58 (6.5) | 27 (5.9) | 31 (7.2) | |
Active or passive smoking (yes) | 6 (0.7) | 3 (0.7) | 3 (0.7) | 0.999 |
Multiparity (yes) | 202 (22.7) | 125 (27.2) | 77 (17.9) | 0.001 |
Vaginal delivery (yes) | 433 (48.2) | 235 (51.2) | 198 (46.1) | 0.142 |
Gravidity | 0.143 | |||
1 | 496 (55.8) | 244 (53.2) | 252 (58.6) | |
2 | 237 (26.7) | 135 (29.4) | 102 (23.7) | |
>2 | 156 (17.5) | 80 (17.4) | 76 (17.7) | |
GDM (yes)b | 95 (10.7) | 53 (11.5) | 42 (9.8) | 0.454 |
Hypertension during pregnancy (yes) | 21 (2.4) | 16 (3.5) | 5 (1.2) | 0.040 |
Preeclampsia (yes) | 11 (1.2) | 5 (1.1) | 6 (1.4) | 0.913 |
Chorioamnionitis (yes) | 2 (0.2) | 0 (0) | 2 (0.5) | 0.451 |
Fasting glucose (mmol/L) | 4.37 ± 0.47 | 4.37 ± 0.44 | 4.37 ± 0.50 | 0.877 |
OGTT 1-h glucose (mmol/L) | 7.01 ± 1.50 | 7.00 ± 1.54 | 7.03 ± 1.45 | 0.699 |
OGTT 2-h glucose (mmol/L) | 6.26 ± 1.23 | 6.21 ± 1.25 | 6.30 ± 1.21 | 0.258 |
Child’s birth weight (kg) | 3.37 ± 0.44 | 3.40 ± 0.42 | 3.31 ± 0.44 | <0.001 |
SGA (yes) | 93 (10.5) | 30 (6.5) | 63 (14.6) | <0.001 |
LGA (yes) | 88 (9.9) | 59 (12.9) | 29 (6.7) | 0.003 |
Macrosomia (yes) | 68 (7.6) | 44 (9.6) | 24 (5.6) | 0.021 |
Children | ||||
Age (years) | 6.0 ± 0.2 | 6.0 ± 0.2 | 6.0 ± 0.2 | 0.831 |
BMI z score | −0.34 ± 1.30 | −0.28 ± 1.41 | −0.41 ± 1.18 | 0.140 |
Breastfeeding duration (months) | 0.145 | |||
≥6 | 590 (66.4) | 297 (64.7) | 293 (68.1) | |
<6 | 168 (18.9) | 84 (18.3) | 84 (19.5) | |
NA | 131 (14.7) | 78 (17.0) | 53 (12.3) | |
Respiratory diseases | 78 (8.8) | 50 (10.9) | 28 (6.5) | 0.029 |
Blood glucose (mmol/L) | 4.59 ± 3.49 | 4.50 ± 0.53 | 4.69 ± 4.99 | 0.414 |
FEV1z-score | 0.25 ± 1.17 | 0.35 ± 1.33 | 0.15 ± 0.96 | 0.011 |
FVC z score | 0.54 ± 1.23 | 0.62 ± 1.38 | 0.46 ± 1.03 | 0.055 |
FEV1/FVC z score | −0.49 ± 1.03 | −0.40 ± 1.08 | −0.60 ± 0.97 | 0.003 |
FEF25-75%z score | 0.25 ± 0.88 | 0.16 ± 0.87 | 0.33 ± 0.89 | 0.004 |
FEV1 <85% of predicted value (yes) | 32 (3.6) | 13 (2.8) | 19 (4.4) | 0.276 |
FVC <85% of predicted value (yes) | 45 (5.1) | 24 (5.2) | 21 (4.9) | 0.935 |
Characteristic . | All (N = 889) . | Boys (n = 459) . | Girls (n = 430) . | P valuea . |
---|---|---|---|---|
Maternal | ||||
Age (years) | 29.1 ± 3.6 | 29.3 ± 3.7 | 29.0 ± 3.6 | 0.223 |
Gestational age (weeks) | 39.3 ± 1.2 | 39.2 ± 1.1 | 39.3 ± 1.2 | 0.269 |
Prepregnancy BMI (kg/m2) | 21.0 ± 2.9 | 21.2 ± 2.9 | 20.9 ± 2.8 | 0.094 |
Gestational weight gain (kg) | 16.1 ± 4.7 | 16.0 ± 4.7 | 16.2 ± 4.7 | 0.552 |
Education level (schooling years) | 0.414 | |||
≤9 | 47 (5.3) | 28 (6.1) | 19 (4.4) | |
10–12 | 186 (20.9) | 102 (22.2) | 84 (19.5) | |
13–15 | 598 (67.3) | 302 (65.8) | 296 (68.8) | |
≥16 | 58 (6.5) | 27 (5.9) | 31 (7.2) | |
Active or passive smoking (yes) | 6 (0.7) | 3 (0.7) | 3 (0.7) | 0.999 |
Multiparity (yes) | 202 (22.7) | 125 (27.2) | 77 (17.9) | 0.001 |
Vaginal delivery (yes) | 433 (48.2) | 235 (51.2) | 198 (46.1) | 0.142 |
Gravidity | 0.143 | |||
1 | 496 (55.8) | 244 (53.2) | 252 (58.6) | |
2 | 237 (26.7) | 135 (29.4) | 102 (23.7) | |
>2 | 156 (17.5) | 80 (17.4) | 76 (17.7) | |
GDM (yes)b | 95 (10.7) | 53 (11.5) | 42 (9.8) | 0.454 |
Hypertension during pregnancy (yes) | 21 (2.4) | 16 (3.5) | 5 (1.2) | 0.040 |
Preeclampsia (yes) | 11 (1.2) | 5 (1.1) | 6 (1.4) | 0.913 |
Chorioamnionitis (yes) | 2 (0.2) | 0 (0) | 2 (0.5) | 0.451 |
Fasting glucose (mmol/L) | 4.37 ± 0.47 | 4.37 ± 0.44 | 4.37 ± 0.50 | 0.877 |
OGTT 1-h glucose (mmol/L) | 7.01 ± 1.50 | 7.00 ± 1.54 | 7.03 ± 1.45 | 0.699 |
OGTT 2-h glucose (mmol/L) | 6.26 ± 1.23 | 6.21 ± 1.25 | 6.30 ± 1.21 | 0.258 |
Child’s birth weight (kg) | 3.37 ± 0.44 | 3.40 ± 0.42 | 3.31 ± 0.44 | <0.001 |
SGA (yes) | 93 (10.5) | 30 (6.5) | 63 (14.6) | <0.001 |
LGA (yes) | 88 (9.9) | 59 (12.9) | 29 (6.7) | 0.003 |
Macrosomia (yes) | 68 (7.6) | 44 (9.6) | 24 (5.6) | 0.021 |
Children | ||||
Age (years) | 6.0 ± 0.2 | 6.0 ± 0.2 | 6.0 ± 0.2 | 0.831 |
BMI z score | −0.34 ± 1.30 | −0.28 ± 1.41 | −0.41 ± 1.18 | 0.140 |
Breastfeeding duration (months) | 0.145 | |||
≥6 | 590 (66.4) | 297 (64.7) | 293 (68.1) | |
<6 | 168 (18.9) | 84 (18.3) | 84 (19.5) | |
NA | 131 (14.7) | 78 (17.0) | 53 (12.3) | |
Respiratory diseases | 78 (8.8) | 50 (10.9) | 28 (6.5) | 0.029 |
Blood glucose (mmol/L) | 4.59 ± 3.49 | 4.50 ± 0.53 | 4.69 ± 4.99 | 0.414 |
FEV1z-score | 0.25 ± 1.17 | 0.35 ± 1.33 | 0.15 ± 0.96 | 0.011 |
FVC z score | 0.54 ± 1.23 | 0.62 ± 1.38 | 0.46 ± 1.03 | 0.055 |
FEV1/FVC z score | −0.49 ± 1.03 | −0.40 ± 1.08 | −0.60 ± 0.97 | 0.003 |
FEF25-75%z score | 0.25 ± 0.88 | 0.16 ± 0.87 | 0.33 ± 0.89 | 0.004 |
FEV1 <85% of predicted value (yes) | 32 (3.6) | 13 (2.8) | 19 (4.4) | 0.276 |
FVC <85% of predicted value (yes) | 45 (5.1) | 24 (5.2) | 21 (4.9) | 0.935 |
Data reported as n (%) or mean (±SD). LGA, large for gestational age; NA, not applicable; SGA, small for gestational age.
aTests for significant differences between offspring sex. Statistically significant values (P < 0.05) are in bold type.
bGDM was diagnosed using the IADPSG criteria with a 75-g OGTT.
Associations Between Maternal GDM and Child Lung Function
Initial analyses explored the relationship between maternal GDM and children's lung function metrics (Table 2). After adjusting for a child’s demographic factors, maternal GDM was negatively associated with the following z scores for the child: FEV1 −0.37 (95% CI, −0.61 to −0.13), FVC −0.36 (95% CI, −0.611 to −0.11), and FEF25-75% −0.25 (95% CI, −0.431 to −0.06). These associations remained substantially consistent after further adjustment for maternal factors during pregnancy, with a slight attenuation of the estimates. Moreover, additional adjustments for the child’s birth weight and blood glucose levels did not significantly alter the observed associations. Sex-stratified analysis indicated that the negative relationships between maternal GDM and child lung function were more pronounced in girls, though the sex-specific effects did not reach statistical significance for interaction (Table S2). Additionally, among children diagnosed with respiratory diseases, maternal GDM showed an inverse relationship with FEV1/FVC z score (−0.72; 95% CI, −1.451 to −0.01). In children without respiratory diseases, maternal GDM was inversely associated with FEV1 (−0.27; 95% CI, −0.541 to −0.01) and FVC (−0.32; 95% CI, −0.601 to −0.04) z scores (Table S3).
Association of maternal GDM during pregnancy with child lung function (N = 889)
GDM z-score parameter . | Model 1a . | Model 2b . | Model 3c . | Model 4d . | ||||
---|---|---|---|---|---|---|---|---|
β (95% CI) . | P value . | β (95% CI) . | P value . | β (95% CI) . | P value . | β (95% CI) . | P value . | |
FEV1 | −0.37 (−0.61 to −0.13) | <0.001 | −0.31 (−0.56 to −0.06) | 0.016 | −0.31 (−0.56 to −0.06) | 0.016 | −0.31 (−0.56 to −0.06) | 0.016 |
FVC | −0.36 (−0.61 to −0.11) | <0.001 | −0.30 (−0.56 to −0.03) | 0.027 | −0.30 (−0.56 to −0.04) | 0.026 | −0.30 (−0.56 to −0.03) | 0.026 |
FEV1/FVC | −0.06 (−0.28 to 0.15) | 0.558 | −0.07 (−0.30 to 0.16) | 0.537 | −0.07 (−0.30 to 0.16) | 0.534 | −0.07 (−0.30 to 0.16) | 0.527 |
FEF25-75% | −0.25 (−0.43 to −0.06) | <0.001 | −0.22 (−0.41 to −0.03) | 0.024 | −0.22 (−0.41 to −0.03) | 0.024 | −0.22 (−0.41 to −0.03) | 0.023 |
GDM z-score parameter . | Model 1a . | Model 2b . | Model 3c . | Model 4d . | ||||
---|---|---|---|---|---|---|---|---|
β (95% CI) . | P value . | β (95% CI) . | P value . | β (95% CI) . | P value . | β (95% CI) . | P value . | |
FEV1 | −0.37 (−0.61 to −0.13) | <0.001 | −0.31 (−0.56 to −0.06) | 0.016 | −0.31 (−0.56 to −0.06) | 0.016 | −0.31 (−0.56 to −0.06) | 0.016 |
FVC | −0.36 (−0.61 to −0.11) | <0.001 | −0.30 (−0.56 to −0.03) | 0.027 | −0.30 (−0.56 to −0.04) | 0.026 | −0.30 (−0.56 to −0.03) | 0.026 |
FEV1/FVC | −0.06 (−0.28 to 0.15) | 0.558 | −0.07 (−0.30 to 0.16) | 0.537 | −0.07 (−0.30 to 0.16) | 0.534 | −0.07 (−0.30 to 0.16) | 0.527 |
FEF25-75% | −0.25 (−0.43 to −0.06) | <0.001 | −0.22 (−0.41 to −0.03) | 0.024 | −0.22 (−0.41 to −0.03) | 0.024 | −0.22 (−0.41 to −0.03) | 0.023 |
Statistically significant values (P < 0.05) are in bold type.
aModel 1 was adjusted for child age, sex, BMI z score, breastfeeding duration, and respiratory diseases.
bModel 2 is model 1 plus maternal variables at pregnancy: age, education, gestational age, prepregnancy BMI, gestational weight gain, method of delivery, parity, gravidity, and smoking.
cModel 3 is model 2 plus child’s birth weight.
dModel 4 is model 3 plus child’s blood glucose levels.
Associations Between Continuous Maternal Glycemia and Child Lung Function
Subsequent analyses examined the relationship between maternal fasting, 1- and 2-h glucose, as well as the sum of glucose z scores during the pregnancy OGTT, and offspring lung function metrics. In the fully adjusted models, negative associations were identified between maternal OGTT 1-h glucose levels, the sum of glucose z scores, and several measures of children's lung function, including z scores for FEV1, FVC, and FEF25-75%. Additionally, maternal OGTT 2-h glucose levels were negatively associated only with the FEV1z score (Table 3). The restricted cubic splines analyses further confirmed linear associations between maternal OGTT 1-h glucose level and both FEV1z score and FVC z score (Fig. S2 and S3). In contrast, maternal fasting plasma glucose levels did not show significant associations with any lung function parameters. However, a piecewise analysis identified a threshold at a fasting blood glucose level of 4.33 mmol/L. Below this threshold, negative associations emerged between fasting blood glucose levels and z scores for FEV1, FVC, and FEF25-75% (Table S4).
Association of continuous maternal measures of glucose during pregnancy with child lung function (N = 889)
Indicator, z score . | Model 1a . | Model 2b . | Model 3c . | Model 4d . | ||||
---|---|---|---|---|---|---|---|---|
β (95% CI) . | P value . | β (95% CI) . | P value . | β (95% CI) . | P value . | β (95% CI) . | P value . | |
Fasting glucose | ||||||||
FEV1 | −0.06 (−0.13 to 0.02) | 0.149 | −0.03 (−0.11 to 0.04) | 0.391 | −0.04 (−0.12 to 0.04) | 0.349 | −0.04 (−0.12 to 0.04) | 0.332 |
FVC | −0.07 (−0.15 to 0.01) | 0.075 | −0.05 (−0.13 to 0.04) | 0.261 | −0.05 (−0.13 to 0.03) | 0.227 | −0.05 (−0.13 to 0.03) | 0.207 |
FEV1/FVC | 0.01 (−0.05 to 0.08) | 0.676 | 0.01 (−0.06 to 0.08) | 0.828 | −0.01 (−0.06 to 0.08) | 0.868 | −0.01 (−0.06 to 0.08) | 0.821 |
FEF25-75% | −0.02 (−0.07 to 0.04) | 0.594 | −0.01 (−0.07 to 0.05) | 0.839 | −0.01 (−0.07 to 0.05) | 0.791 | −0.01 (−0.07 to 0.05) | 0.827 |
OGTT 1-h glucose | ||||||||
FEV1 | −0.12 (−0.20 to −0.05) | <0.001 | −0.11 (−0.19 to −0.03) | 0.007 | −0.11 (−0.19 to −0.03) | 0.006 | −0.11 (−0.19 to −0.03) | 0.005 |
FVC | −0.11 (−0.19 to −0.03) | 0.004 | −0.10 (−0.18 to −0.02) | 0.017 | −0.10 (−0.18 to −0.02) | 0.014 | −0.11 (−0.19 to −0.02) | 0.011 |
FEV1/FVC | −0.03 (−0.10 to 0.03) | 0.314 | −0.04 (−0.11 to 0.04) | 0.317 | −0.04 (−0.11 to 0.03) | 0.301 | −0.03 (−0.10,0.04) | 0.350 |
FEF25-75% | −0.07 (−0.13 to −0.01) | 0.013 | −0.06 (−0.12 to −0.003) | 0.039 | −0.06 (−0.12 to −0.003) | 0.036 | −0.06 (−0.12 to −0.001) | 0.043 |
OGTT 2-h glucose | ||||||||
FEV1 | −0.10 (−0.18 to −0.03) | 0.006 | −0.09 (−0.16 to −0.01) | 0.034 | −0.09 (−0.17 to −0.01) | 0.029 | −0.09 (−0.17 to −0.01) | 0.028 |
FVC | −0.07 (−0.15 to 0.004) | 0.063 | −0.06 (−0.14 to 0.02) | 0.153 | −0.06 (−0.14 to 0.02) | 0.141 | −0.06 (−0.15 to 0.02) | 0.131 |
FEV1/FVC | −0.06 (−0.12 to 0.01) | 0.095 | −0.05 (−0.12 to 0.02) | 0.164 | −0.05 (−0.12 to 0.02) | 0.152 | 0.05 (−0.12 to 0.02) | 0.163 |
FEF25-75% | −0.07 (−0.12 to −0.01) | 0.023 | −0.05 (−0.11 to 0.01) | 0.134 | −0.05 (−0.10 to 0.01) | 0.126 | 0.05 (−0.12 to 0.02) | 0.133 |
Sum of glucose z scores | ||||||||
FEV1 | −0.13 (−0.20 to −0.05) | 0.001 | −0.11 (−0.19 to −0.03) | 0.009 | −0.11 (−0.19 to −0.03) | 0.006 | −0.11 (−0.19 to −0.03) | 0.006 |
FVC | −0.11 (−0.19 to −0.04) | 0.004 | −0.10 (−0.18 to −0.01) | 0.022 | −0.10 (−0.19 to −0.02) | 0.018 | −0.10 (−0.19 to −0.02) | 0.014 |
FEV1/FVC | −0.03 (−0.10 to 0.03) | 0.316 | −0.04 (−0.11 to 0.04) | 0.316 | −0.04 (−0.11 to 0.04) | 0.292 | −0.03 (−0.11 to 0.04) | 0.335 |
FEF25-75% | −0.07 (−0.13 to −0.01) | 0.019 | −0.05 (−0.12,0.01) | 0.084 | −0.06 (−0.11,0.01) | 0.073 | −0.05 (−0.12 to 0.01) | 0.085 |
Indicator, z score . | Model 1a . | Model 2b . | Model 3c . | Model 4d . | ||||
---|---|---|---|---|---|---|---|---|
β (95% CI) . | P value . | β (95% CI) . | P value . | β (95% CI) . | P value . | β (95% CI) . | P value . | |
Fasting glucose | ||||||||
FEV1 | −0.06 (−0.13 to 0.02) | 0.149 | −0.03 (−0.11 to 0.04) | 0.391 | −0.04 (−0.12 to 0.04) | 0.349 | −0.04 (−0.12 to 0.04) | 0.332 |
FVC | −0.07 (−0.15 to 0.01) | 0.075 | −0.05 (−0.13 to 0.04) | 0.261 | −0.05 (−0.13 to 0.03) | 0.227 | −0.05 (−0.13 to 0.03) | 0.207 |
FEV1/FVC | 0.01 (−0.05 to 0.08) | 0.676 | 0.01 (−0.06 to 0.08) | 0.828 | −0.01 (−0.06 to 0.08) | 0.868 | −0.01 (−0.06 to 0.08) | 0.821 |
FEF25-75% | −0.02 (−0.07 to 0.04) | 0.594 | −0.01 (−0.07 to 0.05) | 0.839 | −0.01 (−0.07 to 0.05) | 0.791 | −0.01 (−0.07 to 0.05) | 0.827 |
OGTT 1-h glucose | ||||||||
FEV1 | −0.12 (−0.20 to −0.05) | <0.001 | −0.11 (−0.19 to −0.03) | 0.007 | −0.11 (−0.19 to −0.03) | 0.006 | −0.11 (−0.19 to −0.03) | 0.005 |
FVC | −0.11 (−0.19 to −0.03) | 0.004 | −0.10 (−0.18 to −0.02) | 0.017 | −0.10 (−0.18 to −0.02) | 0.014 | −0.11 (−0.19 to −0.02) | 0.011 |
FEV1/FVC | −0.03 (−0.10 to 0.03) | 0.314 | −0.04 (−0.11 to 0.04) | 0.317 | −0.04 (−0.11 to 0.03) | 0.301 | −0.03 (−0.10,0.04) | 0.350 |
FEF25-75% | −0.07 (−0.13 to −0.01) | 0.013 | −0.06 (−0.12 to −0.003) | 0.039 | −0.06 (−0.12 to −0.003) | 0.036 | −0.06 (−0.12 to −0.001) | 0.043 |
OGTT 2-h glucose | ||||||||
FEV1 | −0.10 (−0.18 to −0.03) | 0.006 | −0.09 (−0.16 to −0.01) | 0.034 | −0.09 (−0.17 to −0.01) | 0.029 | −0.09 (−0.17 to −0.01) | 0.028 |
FVC | −0.07 (−0.15 to 0.004) | 0.063 | −0.06 (−0.14 to 0.02) | 0.153 | −0.06 (−0.14 to 0.02) | 0.141 | −0.06 (−0.15 to 0.02) | 0.131 |
FEV1/FVC | −0.06 (−0.12 to 0.01) | 0.095 | −0.05 (−0.12 to 0.02) | 0.164 | −0.05 (−0.12 to 0.02) | 0.152 | 0.05 (−0.12 to 0.02) | 0.163 |
FEF25-75% | −0.07 (−0.12 to −0.01) | 0.023 | −0.05 (−0.11 to 0.01) | 0.134 | −0.05 (−0.10 to 0.01) | 0.126 | 0.05 (−0.12 to 0.02) | 0.133 |
Sum of glucose z scores | ||||||||
FEV1 | −0.13 (−0.20 to −0.05) | 0.001 | −0.11 (−0.19 to −0.03) | 0.009 | −0.11 (−0.19 to −0.03) | 0.006 | −0.11 (−0.19 to −0.03) | 0.006 |
FVC | −0.11 (−0.19 to −0.04) | 0.004 | −0.10 (−0.18 to −0.01) | 0.022 | −0.10 (−0.19 to −0.02) | 0.018 | −0.10 (−0.19 to −0.02) | 0.014 |
FEV1/FVC | −0.03 (−0.10 to 0.03) | 0.316 | −0.04 (−0.11 to 0.04) | 0.316 | −0.04 (−0.11 to 0.04) | 0.292 | −0.03 (−0.11 to 0.04) | 0.335 |
FEF25-75% | −0.07 (−0.13 to −0.01) | 0.019 | −0.05 (−0.12,0.01) | 0.084 | −0.06 (−0.11,0.01) | 0.073 | −0.05 (−0.12 to 0.01) | 0.085 |
β-Values for child continuous outcomes are reported for maternal fasting and 1- and 2-h glucose values higher by 1 SD. Statistically significant values (P < 0.05) are in bold type.
aModel 1 was adjusted for child age, sex, BMI z score, breastfeeding duration and respiratory diseases.
bModel 2 is model 1 plus maternal variables at pregnancy: age, education, gestational age, prepregnancy BMI, gestational weight gain, method of delivery, parity, gravidity, and smoking.
cModel 3 is model 2 plus child’s birth weight.
dModel 4 is model 3 plus child’s blood glucose levels.
Maternal OGTT Glucose Trajectories and Child Lung Function
Trajectory analysis was conducted to investigate the relationship between maternal glucose response patterns during the OGTT and child lung function outcomes. This analysis identified a best-fit quadratic trajectory for OGTT responses, distinguishing three latent classes (Fig. S4). Class A, forming the majority at 53.6% of the cohort, demonstrated normal glucose tolerance. Class B, accounting for 37.3%, exhibited elevated glucose levels at 1-h and 2-h post-OGTT, and class C, the smallest group at 9.1%, had the most pronounced glucose responses during these periods. Table S5 illustrates the characteristics of mothers and their children's outcomes based on maternal glucose trajectories. The fully adjusted analysis revealed significant associations between these glucose response classes and child lung function metrics, particularly the FEV1z score. Compared with class A, class B had a slightly lower FEV1z score (−0.17; 95% CI, −0.33 to −0.003; P = 0.045), and class C demonstrated more substantial reductions in both FEV1z score (−0.31; 95% CI, −0.60 to −0.02; P = 0.037) and FEF25-75%z score (−0.24; 95% CI, −0.46 to −0.02; P = 0.031) (Table S6).
Association of Maternal Glucose Traits With Impaired Lung Function in Children
Table 4 presents the adjusted odds ratios (ORs) for the risk of lung function impairment in children, based on various maternal glucose indicators. Maternal GDM was associated with a significantly increased risk (OR 2.64; 95% CI, 1.10–5.85) of lung function impairment, indicated by an FVC <85% of the predicted value. Additionally, for every SD increase in the 1-h post-OGTT glucose level, there was an associated increase in the odds of lung function impairment, both for FEV1 <85% of the predicted value (OR 1.44; 95% CI, 1.01–2.08) and for FVC <85% of the predicted value (OR 1.38; 95% CI, 1.01–1.89).
Association of maternal glucose traits during pregnancy with impaired lung function in children (N = 889)
Glucose trait . | FEV1 <85% of predicted value . | FVC <85% of predicted value . | ||
---|---|---|---|---|
OR (95% CI) . | P value . | OR (95% CI) . | P value . | |
GDM | 1.56 (0.48–4.18) | 0.424 | 2.64 (1.10–5.85) | 0.020 |
Fasting glucosea | 1.06 (0.71–1.45 | 0.742 | 1.16 (0.85–1.50) | 0.276 |
OGTT 1-h glucosea | 1.44 (1.01–2.08) | 0.048 | 1.38 (1.01–1.89) | 0.041 |
OGTT 2-h glucosea | 1.28 (0.89–1.80) | 0.164 | 1.0 (0.77–1.44) | 0.712 |
Sum of glucose z scoresa | 1.34 (0.93–1.90) | 0.104 | 1.29 (0.93–1.75) | 0.117 |
Glucose trait . | FEV1 <85% of predicted value . | FVC <85% of predicted value . | ||
---|---|---|---|---|
OR (95% CI) . | P value . | OR (95% CI) . | P value . | |
GDM | 1.56 (0.48–4.18) | 0.424 | 2.64 (1.10–5.85) | 0.020 |
Fasting glucosea | 1.06 (0.71–1.45 | 0.742 | 1.16 (0.85–1.50) | 0.276 |
OGTT 1-h glucosea | 1.44 (1.01–2.08) | 0.048 | 1.38 (1.01–1.89) | 0.041 |
OGTT 2-h glucosea | 1.28 (0.89–1.80) | 0.164 | 1.0 (0.77–1.44) | 0.712 |
Sum of glucose z scoresa | 1.34 (0.93–1.90) | 0.104 | 1.29 (0.93–1.75) | 0.117 |
Model adjusted for child age, sex, BMI z score, breastfeeding duration, respiratory diseases, maternal variables at pregnancy (age, education, gestational age, prepregnancy BMI, gestational weight gain, method of delivery, parity, gravidity, and smoking), child’s birth weight, and child’s blood glucose levels. Statistically significant values (P < 0.05) are in bold type.
aORs are reported for maternal fasting, and 1- and 2-h glucose values higher by 1 SD.
Conclusions
Principal Findings
This comprehensive birth-cohort follow-up study provides novel insights; to our knowledge, it is the first study to examine the association between maternal glycemia during pregnancy and lung function of their offspring at 6 years of age. We found that intrauterine exposure to GDM significantly reduced lung function parameters in children, with more pronounced effects in female offspring. Additionally, maternal GDM increased the risk of impaired lung function development in children, evidenced by an FVC <85% of the predicted value. Furthermore, maternal blood glucose levels at various stages during pregnancy, as determined by OGTT, predominantly had a negative association with lung function in children, particularly affecting postload glucose levels.
Results in the Context of What is Known
The implications of maternal GDM on offspring's health have been extensively documented, linking it to conditions ranging from metabolic syndrome to cardiovascular anomalies (21,22). However, our study addresses a critical gap by exploring the lesser-studied effects of maternal GDM on offspring lung function. Although previous studies have suggested the potential impacts of maternal metabolic conditions on fetal lung development (23), our research provides concrete evidence linking maternal GDM with specific impairments in children’s lung function. Lung function development begins early in pregnancy and continues into the early twenties. Deviations from normal development can lead to chronic lung diseases later in life (24). Factors such as maternal perinatal BMI, neonatal birth weight, and early childhood asthma play crucial roles in shaping lung development, which emphasizes the critical importance of exposures during prenatal stages and early life in determining respiratory health outcomes (5,25). Recent research has begun to uncover the adverse effects of maternal hyperglycemia on fetal lung development, with in vitro studies showing that hyperglycemic conditions can negatively affect fetal lung angiogenesis, essential for normal lung maturation (26). Animal models have further revealed that offspring of mothers with diabetes experience substantial pulmonary function impairments, disrupted lung epithelial cell differentiation, and increased oxidative stress levels, illustrating the detrimental effects of maternal diabetes on lung development (27).
Moreover, the relationship between diabetes mellitus and reduced lung function extends beyond the prenatal period into adulthood, suggesting a broader association between metabolic and respiratory health (28,29). This association has been supported by large-scale studies suggesting that high blood glucose levels can directly affect lung function and pointing to a causal link between type 2 diabetes and decreased lung capacity (30). Our study builds on these insights, highlighting the complex relationship between maternal GDM and the lung development of offspring. It underscores the importance of optimal glycemic control during pregnancy to support the respiratory health of the next generation.
Our findings reveal sex-specific variations and differences at distinct OGTT stages of the impact of GDM on children's lung function. Consistent with previous studies, such sex-related disparities may arise from the distinct effects of estrogen and testosterone, which critically influence lung development and maturation, leading to varied impacts of maternal GDM based on the offspring's sex (31–33). The differences observed at various OGTT stages might reflect levels of fetal exposure to hyperglycemia, affecting lung development differently (34,35). Although these observations offer valuable insights, the precise biological mechanisms remain to be fully uncovered, highlighting the need for further research to delineate the specific pathways involved.
The mechanisms underlying the observed associations remain speculative but may involve several biological pathways. GDM results in hyperglycemia, which can lead to fetal hyperinsulinemia and subsequent overgrowth, potentially affecting lung development (36,37). Moreover, maternal hyperglycemia may induce oxidative stress and inflammation, further impairing fetal lung maturation and function (38,39). These processes might not only affect lung structure and function at birth but could also have lasting effects, predisposing to chronic respiratory conditions later in life.
Clinical Implications
The findings from this study highlight the critical importance of maintaining optimal glycemic control during pregnancy. This is essential not only to prevent immediate adverse obstetric and neonatal outcomes but also to address potential long-term health implications for offspring. Given the association between maternal GDM and impaired lung function in children, health care providers should consider incorporating lung function monitoring into the routine follow-up of children born to mothers with GDM. This proactive approach could facilitate early intervention, potentially improving respiratory outcomes and enhancing the quality of life for these children.
Research Implications
Our study underscores the necessity for further research to explore the mechanisms by which maternal GDM influences lung development and function in offspring. Studies should aim to elucidate the biological pathways involved, including the potential roles of fetal hyperinsulinemia, oxidative stress, and inflammation. Moreover, intervention studies are needed to determine if specific strategies for managing maternal glucose levels during pregnancy can mitigate the adverse effects on offspring's lung function. Additionally, it would be valuable to examine the impact of maternal GDM on lung function beyond early childhood to understand the long-term respiratory health trajectories.
Strengths and Limitations
This study benefits from its prospective cohort design; thorough adjustment for confounders, including birth weight and child glucose levels; and the application of standardized protocols for lung function assessment. Nonetheless, several limitations should be acknowledged. First, the potential lack of generalizability due to the study's specific geographic location and homogeneous population may limit the applicability of the findings to broader populations. Second, the absence of data on factors such as maternal lung function, maternal diet, air pollution, and genetic predispositions could have affected the study's outcomes, but these variables were not accounted for. Third, we could not ascertain the insulin treatment status for patients with GDM in this study; however, it is noted that the majority were treated with only dietary and exercise interventions (40). Fourth, our follow-up is still ongoing and currently encompasses only a small portion of participants; thus, this subgroup (8.9% of our birth cohort) might consist predominantly of children at higher risk for lung function impairment. Finally, we recognize that our data lack information on whether children had COVID-19 or other respiratory illnesses, such as influenza and respiratory syncytial virus, which potentially could have affected lung function outcomes. Future research should include these variables to better assess their impact on lung function in the context of maternal GDM.
Conclusion
In summary, our study provides compelling evidence that maternal GDM is associated with impaired lung function in offspring at 6 years of age. These findings emphasize the significance of optimal glycemic control during pregnancy for the immediate health benefits for both mother and child, as well as for potentially influencing long-term respiratory health in offspring. More research is needed to elucidate the underlying mechanisms of this association and to explore potential interventions to mitigate its effects.
This article contains supplementary material online at https://doi.org/10.2337/figshare.26528128.
Article Information
Funding. This study was supported by the Central Guidance on Local Science and Technology Development Fund of Hubei Province (no. 2022BGE261), the Top Medical Young Talents (2019) of Hubei Province, Wuhan Municipal Health Commission (no. WG21D06) and the Wuhan Talents program (2021).
Duality of Interest. No potential conflicts of interest relevant to this article were reported.
Author Contributions. M.Y. and Z.C. performed the statistical analyses, interpreted the data, and drafted the manuscript. W.L., X.C., J.Z., J.L., Y. Zhou, and Y. Zhong contributed to the data acquisition and review for important intellectual content. L.S. and R.L. revised the manuscript. H.X. and A.Z. conceived and designed this study, and final version approval. All authors have read and approved the final manuscript. H.X. and M.Y. are the guarantors of this work and, as such, had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Handling Editors. The journal editors responsible for overseeing the review of the manuscript were John B. Buse and Kristen J. Nadeau.