Association between gestational weight gain and metabolic and inflammatory biomarkers in the ETCHED cohort

Gestational weight gain (GWG) is a critical determinant of maternal and neonatal health, with both excess (EGWG) and inadequate GWG (IGWG) linked to adverse pregnancy outcomes and metabolic risk. We investigated the association between maternal prenatal demographic, clinical, and metabolic biomarkers at baseline, and GWG in singleton pregnancies from the Early Tracking of Childhood Health Determinants (ETCHED) life-course cohort. GWG, defined as the difference between pregestational and pre-delivery weight, was the primary outcome. Among 120 eligible mothers, 79.2% self-identified as Hispanic and 16.0% as American Indian/Alaska Native. The cohort represented socioeconomically disadvantaged populations: 75% had a high school education or less, 31% were single mothers, and 52.5% reported an annual household income < $25,000. Compared with mothers with normal GWG, those with EGWG had significantly higher leptin and lower IL-8 levels (P < 0.05). A multivariate multinomial logistic regression identified leptin to be strongly associated with EGWG (OR/1 SD: 11.09; 95%CI 3.18–38.67; P = 0.001), followed by FGF21, IL8, and pregestational BMI. Higher cortisol levels were associated with increased risk of IGWG (OR/1 SD: 2.59; 95%CI 1.07–6.29; P = 0.03). EGWG was associated with higher rates of cesarean delivery and prematurity. These findings highlight distinct metabolic and inflammatory biomarkers associated with GWG in an understudied population.

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Publication Details

Journal
Scientific Reports
Published
2026-02-25
DOI
https://doi.org/10.1038/s41598-026-41560-w
Primary Topic
Gestational Diabetes Research and Management
Type
article
Field-Weighted Citation Impact
0.00

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article

Association between gestational weight gain and metabolic and inflammatory biomarkers in the ETCHED cohort

Dorota Wasak, Yunhua L. Muller, Robert L. Hanson, William C. Knowler et al.
Scientific Reports
Gestational Diabetes Research and Management
article

Association between gestational weight gain and metabolic and inflammatory biomarkers in the ETCHED cohort

Dorota Wasak, Yunhua L. Muller, Robert L. Hanson, William C. Knowler, Madhumita Sinha, Rachel Caballero, Sourav RoyChoudhury, Zaqueena Coleman, Marilyn Q. Sale
article en

Abstract

Gestational weight gain (GWG) is a critical determinant of maternal and neonatal health, with both excess (EGWG) and inadequate GWG (IGWG) linked to adverse pregnancy outcomes and metabolic risk. We investigated the association between maternal prenatal demographic, clinical, and metabolic biomarkers at baseline, and GWG in singleton pregnancies from the Early Tracking of Childhood Health Determinants (ETCHED) life-course cohort. GWG, defined as the difference between pregestational and pre-delivery weight, was the primary outcome. Among 120 eligible mothers, 79.2% self-identified as Hispanic and 16.0% as American Indian/Alaska Native. The cohort represented socioeconomically disadvantaged populations: 75% had a high school education or less, 31% were single mothers, and 52.5% reported an annual household income < $25,000. Compared with mothers with normal GWG, those with EGWG had significantly higher leptin and lower IL-8 levels (P < 0.05). A multivariate multinomial logistic regression identified leptin to be strongly associated with EGWG (OR/1 SD: 11.09; 95%CI 3.18–38.67; P = 0.001), followed by FGF21, IL8, and pregestational BMI. Higher cortisol levels were associated with increased risk of IGWG (OR/1 SD: 2.59; 95%CI 1.07–6.29; P = 0.03). EGWG was associated with higher rates of cesarean delivery and prematurity. These findings highlight distinct metabolic and inflammatory biomarkers associated with GWG in an understudied population.

Scientific Reports
National Institute of Diabetes and Digestive and Kidney Diseases (US)
U.S. Department of Health and Human Services, National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases
Zero hunger
Openalex Percentile: Top 40%
Gestational Diabetes Research and Management
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