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. Author manuscript; available in PMC: 2026 Jun 9.
Published in final edited form as: Matern Child Health J. 2026 May 20;30(6):780–789. doi: 10.1007/s10995-026-04263-2

Maternal Inflammatory Biomarkers at 28 Weeks of Pregnancy and Childhood Adiposity at Age 7 and 13 Years in the Seychelles Child Development Study

M Kahwaji 1, EM McSorley 2, AJ Yeates 2, MS Mulhern 2, T Spence 2, W Crowe 2, P Allsopp 2, E Shroff 3, C Shamlaye 3, JJ Strain 2, E van Wijngaarden 1
PMCID: PMC13244653  NIHMSID: NIHMS2179011  PMID: 42159873

Abstract

Introduction:

Dysregulated inflammation during pregnancy can result in an adverse intrauterine environment, potentially disrupting fetal growth and development and increasing the risk of childhood obesity. This study aimed to assess the association between maternal inflammation during the second trimester of pregnancy and childhood adiposity at ages 7 and 13 years.

Methods:

Utilizing the Seychelles Child Development Study Nutrition Cohort 2 (SCDS NC2), we measured maternal inflammatory markers (IL-1β, IL-2, IFN-γ, TNF-α, IL-4, IL-5, IL-10, IL-6, CRP, MCP-1, sFlt-1, and VEGF-D) at 28 weeks gestation and childhood body mass index (BMI)-for-age z-scores, waist-to-hip circumference ratios, and the odds of overweight and obesity at ages 7 and 13 years. The associations between maternal inflammatory markers and childhood adiposity measures were analyzed using linear regression for BMI-for-age z-scores and waist-to-hip ratios and multinomial logistic regression for weight status. Potential effect modification by child sex was explored using interaction terms.

Results:

Among the 1,351 mother-child pairs, 57.1% of mothers, 12.3% of children at age 7 years, and 15.0% of children at age 13 years were classified with obesity. Few associations between gestational inflammatory markers and any adiposity outcome were statistically significant, and all beta coefficients were close to the null. Several associations had statistically significant sex interaction terms (p < 0.05), however most of these associations were not statistically significant.

Discussion:

Overall, there was no evidence of an association between second trimester maternal inflammatory markers and childhood adiposity at age 7 or 13 years in this cohort.

Keywords: Adiposity, obesity, inflammatory markers, children, pregnancy

Background

Over the past several decades, an increasingly obesogenic environment has contributed to an increase in global childhood obesity (Collaboration, 2017; Di Cesare et al., 2019). This is likely due to a combination of environmental, behavioral, and genetic influences (Di Cesare et al., 2019; Organization, 2016; Sheikh et al., 2017; Swinburn, 2008). The abnormal tissue expansion associated with obesity has been implicated in the etiology of several chronic metabolic conditions, most notably type II diabetes and cardiovascular disease (Caprio et al., 2020; Chen et al., 2023). Consequently, children with obesity or overweight are more likely to be adults with obesity and are at greater risk of other chronic health conditions, such as diabetes, coronary heart disease, and certain cancers, compared to children with normal weight (de Onis et al., 2007; Llewellyn et al., 2016; Weihrauch-Bluher et al., 2019).

In normal pregnancy, the complex balance of anti-inflammatory and pro-inflammatory states protects the mother from infections and promotes optimal fetal growth and development (Mor et al., 2017; Rusterholz et al., 2007). The maternal cytokine milieu varies throughout pregnancy to align with the developmental requirements with pro-inflammatory cytokines supporting embryo implantation and labor; whilst an anti-inflammatory cytokine profile predominates mid- pregnancy. These stage-specific immune transitions make a significant contribution to healthy development and delivery (Parisi et al., 2021; Segovia et al., 2017). Abnormally increased concentrations of pro-inflammatory cytokines and/or decreased concentrations of anti-inflammatory cytokines can lead to chronic placental inflammation and an adverse intrauterine environment for the offspring throughout the course of pregnancy (Parisi et al., 2021; Segovia et al., 2017; Spence et al., 2021). Inflammatory-related cytokines circulating in the mother can pass through the placental barrier, interfering with embryo implantation, placental nutrient transfer, and fetal metabolic programming (Ingvorsen et al., 2015; Robertson et al., 2018). Experimental and observational evidence suggests that a chronic pro-inflammatory state during pregnancy can increase the offspring’s susceptibility to childhood obesity by altering adipogenesis and cytokine expression, programming appetite dysregulation and decreasing insulin receptor expression (Catalano & Shankar, 2017; Parisi et al., 2021; Segovia et al., 2017).

Pro-inflammatory cytokines, those associated with T helper cell type 1 (Th1)-mediated reactions, have been both positively and negatively associated with childhood and early adulthood adiposity in previous epidemiologic studies. Higher concentrations of maternal interferon-gamma (IFN-γ) in early pregnancy were associated with lower BMI-for-age z-scores, while higher levels of interleukin (IL)-17A, IL-10, and IL-6 during gestation were linked to higher BMI-for-age z-scores in children under 10 years and young adults (Danielsen et al., 2014; Ghassabian et al., 2020; Maguire et al., 2021). Anti-inflammatory cytokines, characterized by T helper cell type 2 (Th2)-mediated reactions, have also been both positively and negatively associated with adiposity in previous studies. Higher maternal concentrations of IL-4 and IL-13 at 34 weeks gestation were associated with a reduced risk of being overweight, whereas increased maternal IL-6 concentrations during the third trimester have been linked to higher BMI in young adulthood (Danielsen et al., 2014; Englich et al., 2017). One study measuring c-reactive protein (CRP) during the second trimester in women reported no association with BMI-for-age z-scores during early- (3–5 years) or mid- (7–10 years) childhood (Gaillard et al., 2016).

The inconsistencies in the directions of these results may be partially related to the differing metrics of childhood adiposity, which capture different aspects of body fat accumulation (Jensen et al., 2016; Martin-Calvo et al., 2016). For example, two studies measured waist circumference and only one of these studies measured waist circumference at multiple time points (Danielsen et al., 2014; Gaillard et al., 2016). Further, none of these studies reported adiposity measures during adolescence, which is an important window for predicting obesity and other chronic health conditions in adulthood (Llewellyn et al., 2016; Simmonds et al., 2016; Twig et al., 2016).

We investigated the association between maternal inflammatory biomarkers measured during the second trimester of pregnancy and subsequent childhood adiposity at age 7 and 13 years in the Seychelles Child Development Study Nutrition Cohort 2 (SCDS NC2). We hypothesized that higher concentrations of pro-inflammatory markers and lower concentrations of anti-inflammatory markers would be associated with higher BMI-for-age z-scores, higher waist-to-hip ratios, and greater odds of overweight and obesity at age 7 and 13 years.

Methods

Study Population

As described previously, pregnant women were recruited during their first antenatal visit (beginning at 14 weeks gestation) from 2008 to 2011 (Strain et al., 2021; Strain et al., 2015). The inclusion criteria included being native Seychellois, being at least 16 years of age, having a singleton pregnancy, and having no obvious health concerns (Strain et al., 2015). The current analysis was limited to mother-child pairs with data for gestational inflammatory biomarkers (range: 20.1–33.3 weeks) and adiposity measures at age 7 (range: 7.0–7.9 years) or 13 years (range: 12.5–14.9 years). Two women with unusually high concentrations for most inflammatory markers were excluded from this analysis. Mother-child pairs were excluded if birthweight was less than 1,500 grams, pre- or postnatal death occurred, there were maternal perinatal complications, having a twin birth, the child experienced seizures, or consent was withdrawn. The study was reviewed and approved by the Seychelles Ethics Board and the Research Subjects Review Board at the University of Rochester (#RSRB00055687; continuing review #CR00007863). The research presented was performed in accordance with the ethical standards presented in the Declaration of Helsinki and its subsequent amendments.

Maternal Inflammatory Markers

Non-fasting maternal blood samples were collected at an average 28 weeks of gestation (SD=1.1) by antecubital venipuncture into evacuated serum tubes and analyzed as described previously. (McSorley et al., 2018) Samples were placed on water ice and sat for 30 minutes prior to being centrifuged at 2,500 rpm for 15 minutes. Then, aliquots were shipped to Ulster University (Coleraine, Northern Ireland) at −80°C for storage. Approximately five years after storage, serum inflammatory markers were analyzed using Meso Scale Discovery (MSD) multiplex assay. Fresh, not previously thawed aliquot was used for each participant ID to avoid freeze thaw cycles and minimize any effects of long-term storage on cytokine concentrations.

Inflammatory markers were originally selected for assessment based on reported associations with methylmercury exposure and n-3 long-chain polyunsaturated fatty acid status, which were the original factors of interest in the NC2 study with the primary purpose of studying child neurodevelopment (Nyland, Fillion, et al., 2011; Nyland, Wang, et al., 2011; Strain et al., 2015). These inflammatory biomarkers included cytokines from the major subsets of T helper (TH) cells, Th1 and Th2. Cytokines with Th1 cell activity included IL-1β, IL-2, IFN-γ and tumor necrosis factor-α (TNF-α). Cytokines with Th2 cell activity included IL-4, IL-5, and IL-10. IL-6 was measured and has been shown to have a role in both Th1 and Th2 responses (Chang, 2007; Diehl & Rincon, 2002; Muniroh et al., 2015). Additional inflammatory biomarkers included CRP, monocyte chemoattractant protein 1 (MCP-1), angiogenesis marker soluble fms-like tyrosine kinase 1 (sFlt-1), and vascular endothelial growth factor D (VEGF-D). Inflammatory biomarkers were analyzed as continuous variables measured in pg/ml, except for CRP was measured in mg/L. Values below the lower limit of detection (LLOD) were imputed as LLOD/√2.

Child Anthropometric Measures

Height (cm), weight (kg), hip circumference (cm), and waist circumference (cm) were measured at age 7 years (range 7.04–7.93 years) and age 13 years (range 12.5–14.9) by trained nurses. Waist and hip circumference were measured at the smallest and largest diameter of the waist, respectively. Waist-to-hip ratio was then calculated using these values. Height and weight were used to calculate BMI (kg/m2), which was standardized to BMI-for-age and sex z-scores using WHO guidelines (de Onis et al., 2007). Childhood overweight and obesity were defined as greater than 1 and 2 standard deviations above the WHO Growth Reference median, respectively (de Onis et al., 2007). Based on these guidelines, twelve children at each time point were removed from the analysis for having implausible BMI z-scores (−5 ≥ BMI-for-age ≥ 5) (de Onis et al., 2007).

Covariates

Maternal parity, smoking status, and child sex were self-reported at enrollment using questionnaires administered by trained nurses. At approximately 20 months postpartum, Hollingshead socioeconomic status was assessed using a modified index relevant to the Republic of Seychelles by combining previously described occupational and educational codes to create a continuous score (Davidson et al., 1998). Maternal age, height, and weight were also measured at 20 months postpartum. Previous analyses have shown that pre-pregnancy and postpartum BMI are correlated in the SCDS cohort, so postpartum BMI was used as a proxy for maternal pre-pregnancy BMI (Davidson et al., 2008; McSorley et al., 2018). The sample had a small percentage of smokers (1%) with a large proportion of missingness (6.6%). Thus, smoking status was not considered as a covariate for this analysis.

Potential covariates were selected a priori based on existing literature and directed acyclic graph (DAG) methodology (Greenland et al., 1999). The minimum sufficient set of confounders to control for confounding included maternal age at 20 months postpartum, maternal postpartum BMI, child sex and Hollingshead socioeconomic status (Fall et al., 2015; Gaillard et al., 2014; Keenan-Devlin et al., 2022; Rebholz et al., 2012). Maternal BMI was categorized using the WHO guidelines for descriptive purposes but was included in statistical models as a continuous variable (kg/m2) (WHO, 2023). Gestational age at blood draw (weeks) and the child’s exact age at adiposity measurement (months) were included as covariates to account for any variation in inflammation across the second trimester or adiposity measured at various ages within each range.

Statistical Analysis

Measures of central tendency and variance were used to describe the study sample’s characteristics. Inflammatory biomarkers were transformed by taking the natural logarithm of the value plus a constant of one. Pearson correlations between child adiposity measures at age 7 and 13 years were computed.

The associations between gestational inflammatory markers and adiposity measures were analyzed using linear regression and included participants with no missing data for the specified exposure, outcome, and covariates. To assess any potential nonlinearity in the association, regression models were repeated using quartiles of inflammatory markers in addition to the models with continuous variables. IL-2 and IL-4 were not analyzed by quartile due to the high percentage of values below the lower limit of detection (< 30% detected). The association between gestational inflammatory markers and childhood overweight and obesity was analyzed using multinomial logistic regression. The reference category included those with normal weight or underweight, defined by BMI-for-age z-scores less than 1 standard deviation above the WHO growth reference median (de Onis et al., 2007).

The gestational inflammatory environment has been observed to be different between pregnancies with male and female fetuses (Enninga et al., 2015; Jarmund et al., 2021). To explore potential effect modification by child sex, interaction terms that reached statistical significance (p-value < 0.05) were included in models. All analyses were conducted in SAS 9.4 and figures were created using R version 4.4.

Results

Maternal inflammatory markers, adiposity outcomes, and relevant covariates are summarized in Tables 1–3. On average, mothers were 29 years old at the first visit and blood samples were collected at a mean of 28 weeks gestation. More than half of mothers had overweight or obesity (57. 1%) at 20 months postpartum. Nearly half of mothers were nulliparous (47.3%) and delivered male infants (51.9%).

Table 1.

Descriptive summary of covariates and adiposity outcomes.

Variable N (%) or Mean (SD) Missing
Maternal age at first visit (years) 28.8 (6.3) 17
Hollingshead socioeconomic status 31.9 (10.3) 17
Gestational age at maternal blood draw (weeks) 27.9 (1.14) 28
Smoking status during pregnancy 91
Yes 13 (1.0%)
No 1255 (99.0%)
Parity 16
0 635 (47.3%)
1 401 (29.9%)
2 191 (14.2%)
3 or more 116 (8.6%)
Maternal BMI (kg/m2) at 20 months postpartum1 27.0 (6.59) 76
Underweight (BMI < 18.5 kg/m2) 78 (6.1%)
Normal weight (18.5 ≤ BMI < 25 kg/m2) 473 (36.9%)
Overweight (BMI ≥ 25 kg/m2) 359 (28.0%)
Obesity (BMI ≥ 30 kg/m2) 373 (29.1%)
Child exact age at visit (years) 7.36 (0.21)
Child Sex
Female 654 (48.1%)
Male 705 (51.9%)
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Continuous variables are described using mean and standard deviation (SD). Categorical variables are described using count and percentage.

1

Maternal BMI categorization based on WHO guidelines for adults (WHO, 2023).

Table 3.

Summary of maternal inflammatory markers measured at 28 weeks gestation

Inflammatory Marker1 n Median (SD) LLOD (% detected) Inter-Assay CV (%) Intra-Assay CV (%)
CRP 1340 2.70 (2.71) 1.00 (83.1%) 3.5 <1.8
IL-4 1351 0.01 (0.76) 0.02 (28.6%) 15.28 <30
IL-6 1351 0.52 (91.49) 0.06 (86.5%) 22.96 <28
IL-10 1351 0.90 (7.37) 0.03 (89.8%) 16.48 <20
MCP-1 1351 59.06 (89.98) 0.09 (98.7%) 7.72 <20
TNF-α 1351 6.18 (15.02) 0.04 (99.2%) 16.14 <22
VEGF-D 1351 656.27 (368.99) 2.53 (100%) 17.41 <15
IL-1β 1351 0.19 (4.38) 0.04 (73.2%) 44.38 <26
sFlt-1 1351 1789.02 (1217) 0.56 (100%) 12.54 <22
TARC 1351 77.68 (141.10) 0.22 (97.9%) 22.2 <15
IFN-γ 1351 2.76 (17.47) 0.20 (82.9%) 22.29 <20
IL-2 1351 0.06 (0.59) 0.09 (28.9%) 25.46 <35
IL-5 1351 0.78 (2.20) 0.22 (86.0%) 11.87 <17
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For descriptive purposes, raw, unadjusted values were used for summary statistics. Serum inflammatory biomarkers were measured in pg/mL except CRP (measured in mg/L).

Abbreviations:

LLOD: lower limit of detection; CV: coefficient of variation.

Child BMI z-scores at age 7 years had a median value of 0.28 (SD = 1.55) with 14.8% of children having overweight and 12.3% having obesity. The median BMI z-score at age 13 years was 0.01 (SD = 1.69) with 14.2% of children having overweight and 15.0% of children having obesity. The median waist-to-hip ratio was 0.87 (SD = 0.06) at age 7 years and 0.82 (SD = 0.06) at age 13 years. A larger proportion of children were classified with thinness at age 13 years (10.5%) than at age 7 years (4.1%). BMI-for-age z-scores were highly correlated at ages 7 and 13 years (r=0.82). Waist-to-hip ratios at age 7 were marginally correlated with waist-to-hip ratios at age 13 (r=0.18). BMI-for-age z-scores and waist-to-hip ratios were not correlated at age 7 years (r=0.08). At age 13 years, BMI-for-age z-scores were marginally correlated with waist-to-hip ratios (r=0.22).

At age 7 years, all inflammatory markers, except for IL-5, were not associated with BMI-for-age z-scores and waist-to-hip ratios with beta coefficients close to zero (Figures 1, 2). A one log(pg/mL+1) increase in IL-5 was associated with a 0.193 SD decrease in BMI-for-age z-score (95% Cl: −0.352, −0.034) at age 7 years. Several associations between gestational inflammatory markers and child adiposity outcomes differed by child sex (interaction term p-value <0.05). These sex-specific associations were not statistically significant, except for the association among females between sFlt-1 and BMI-for-age. In models estimating BMI-for-age z-scores, beta coefficients were negative among male children [βIL-2 (95% CI)= −0.162 (−0.578, 0.253); βsFlt-1 (95% CI)= −0.054 (−0.256, 0.148)] and positive among female children, [βsFlt-1 (95% CI) = 0.248 (0.040, 0.457)] and [βIL-2 (95% CI) = 0.346 (−0.074, 0.765)]. Associations between IL-10 and waist-to-hip ratio were negative among females [β (95% CI)= −0.004 (−0.013, 0.004)] and positive among males [β (95% CI) = 0.007 (−0.000, 0.014)].

Figure 1. Linear regression models for continuous maternal inflammatory markers at 28 weeks gestation and child BMI-for-age z-scores at age 7 and 13 years.

Figure 1.

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All inflammatory markers were natural logarithm transformed after adding one to raw values. Regression estimates and 95% confidence intervals are untransformed values after adjustment for maternal BMI at 20 months postpartum, Hollingshead socioeconomic status, maternal age at first visit, gestational age at maternal blood draw, exact child age at adiposity measurement, and child sex. Sex-specific estimates are presented for models that had significant inflammatory marker*sex interaction terms (p<0.05).

Figure 2. Linear regression models for continuous maternal inflammatory markers at 28 weeks gestation and child waist-to-hip ratios at age 7 and 13 years.

Figure 2.

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All inflammatory markers were natural logarithm transformed after adding one to raw values. Regression estimates and 95% confidence intervals are untransformed values after adjustment for maternal BMI at 20 months postpartum, Hollingshead socioeconomic status, maternal age at first visit, gestational age at maternal blood draw, exact child age at adiposity measurement, and child sex. Sex-specific estimates are presented for models that had significant inflammatory marker*sex interaction terms (p<0.05).

Multinomial logistic regression models estimating the odds of being classified with overweight or obesity compared to those with normal weight at age 7 years were consistent with results from models analyzing continuous markers of adiposity and all odds ratios were close in magnitude to the null value of 1 (Supplemental Figure 3). Interactions by sex (p<0.05) were present in associations between IL-5 and sFlt-1 concentrations and the odds of obesity at age 7 years. The associations between these inflammatory markers and the odds of being classified with obesity tended to be positive among females and negative among males, although the associations were not statistically significant except for the association between IL-5 and the odds of obesity among males [OR (95% CI) =0.41 (0.23, 0.74)].

At age 13 years, continuous inflammatory markers were not associated with BMI-for-age and none of these associations varied by sex (Figure 1). There were few observed associations between continuous inflammatory markers and waist-to-hip ratio at age 13 years, although all beta coefficients were close to the null (Figure 2). A one log(pg/ml+1) increase in IL-10 was associated with a 0.007 decrease (95% Cl: −0.013, −0.000) in waist-to-hip ratio at age 13 years. The association between IL-2 and waist-to-hip ratio was positive among females [β (95% CI) = 0.024 (0.003, 0.045)] and negative among males [β (95% CI)= −0.008 (−0.029, 0.013)].

At age 13 years, the results from multinomial logistic regression models estimating the odds of being classified with overweight or obesity compared to those with normal weight at age 13 years were not consistent with results from models analyzing continuous adiposity outcomes (Supplemental Figure 4). All odds ratios were close to the null value of 1 and the associations between maternal inflammatory markers measured at 28 weeks gestation and the odds of overweight and obesity were not statistically significant, except for the associations between IL-5 and the odds of obesity among males [OR (95% CI) = 0.39 (0.22, 0. 70)] and IL-4 and the odds of obesity among females [OR (95% CI) = 3.48 (1.21, 10.01)]. Interactions by sex (p<0.05) were present in associations between IL-4 and IL-5 concentrations and the odds of obesity and IL-10 concentrations and the odds of overweight at age 13 years. All other sex-specific associations were not statistically significant and had odds ratios that were close to the null value of 1.

At both 7 and 13 years, patterns of association were similar when the inflammatory markers were categorized into quartiles. There was little evidence of nonlinearity in associations between gestational inflammatory markers and continuous adiposity markers at 7 and 13 years (Supplemental Figures 1, 2).

Discussion

We examined BMI-for-age z-scores, obesity and overweight, and waist-to-hip ratio in children at age 7 and 13 years. The associations between maternal concentrations of inflammation biomarkers and these outcomes were, in general, not statistically significant and effect estimates were small in magnitude.

BMI-for-age z-scores were not well correlated with waist-to-hip ratios in this cohort. BMI is a crude measure of total adiposity, whereas waist-to-hip ratio is a measure of central adiposity (Jensen et al., 2016; Martin-Calvo et al., 2016). Although BMI-for-age z-scores and waist-to-hip ratios were not well correlated, there were no major differences in their respective associations with inflammatory markers in this cohort. A similar study of pregnant women sampled from Massachusetts, US (n=1, 116) also found consistent results between third trimester CRP concentrations and BMI-for-age z-scores and waist circumference during early- (3–5 years) and mid- (7–10 years) childhood, but the correlation coefficient for BMI-for-age z-scores and waist circumference was not reported. (Gaillard et al., 2016) This study reported a positive association between CRP concentrations measured during the second trimester and BMI-for-age z-scores, whereas no associations were observed with second trimester CRP concentrations in our study (Gaillard et al., 2016). These discrepancies may be explained by the differences in immunological response throughout the course of pregnancy that may be influenced by multiple factors, including maternal infection and gestational age (Mor et al., 2017; Spence et al., 2021). Future studies should continue to explore vulnerable windows of exposure during pregnancy that may be associated with infant growth and development.

Maternal inflammatory marker concentrations and childhood adiposity patterns tend to vary by child sex (Chang et al., 2018; Enninga et al., 2015; Jarmund et al., 2021; Orsso et al., 2020). In our cohort, associations with significant sex interactions tended to be positive among females and negative among males, regardless of whether gestational inflammatory markers had Th1 or Th2 activity. Specifically, negative effect estimates among males and positive effect estimates among females were observed for adiposity measures and IL-2, a Th1 cytokine, as well as IL-5 and IL-4, Th2 cytokines. We also observed that IL-10, a Th2 cytokine, was positively associated with waist-to-hip ratio at age 7 and greater odds of obesity at age 13 among males, although these associations were not statistically significant. A study in a New England cohort (n=1,366) found that the association between second or third trimester maternal TNF-α concentrations, a Th1 cytokine, and BMI z-scores from birth through age 8 years was negative in males and positive in females (Ghassabian et al., 2020). Overall, the sex-specific mechanism for gestational inflammation and adiposity development requires elucidation in future studies.

This study had several strengths. First, the SCDS NC2 is a longitudinal cohort with a large sample and wide distribution of maternal and child adiposity. Secondly, a large panel of inflammatory markers were quantified in maternal serum, allowing for a comprehensive examination of maternal inflammation status. Multiple measures of adiposity (BMI, waist-to-hip ratio, and categorical weight status) at two time points (7 and 13 years) were employed to reduce outcome misclassification. Finally, the large sample size of the SCDS NC2 allowed for the adjustment of covariates of interest and the assessment of sex differences.

There were also limitations to this study. Inflammatory biomarker levels during gestation fluctuate and it is unclear when, or if, disruptions in inflammatory biomarker levels are predictive of obesity development in offspring (Mor et al., 2017). A single measure of gestational inflammation likely does not capture changes in inflammatory cytokine concentrations and may not accurately reflect the child’s true exposure to gestational inflammation (Parisi et al., 2021; Segovia et al., 2017). This study only measured inflammatory markers during the second trimester, which potentially missed disruptions in other stages of gestation. Additionally, this study did not account for maternal diet during pregnancy, which is an important source of maternal inflammation that contributes to the developmental programming of adiposity (Fossee et al., 2023; Harmancioglu & Kabaran, 2023; Shivappa et al., 2015). This exposure misclassification is thought to be minimal given the measurement of inflammatory biomarkers in maternal blood. Additional factors, such as child diet, exercise habits, and pubertal status, and paternal BMI may be predictors of childhood adiposity that were not measured in this study. However, these factors occur after the measurement of maternal inflammatory status during pregnancy and therefore cannot be confounders of the association between maternal inflammatory markers and childhood adiposity. These variables are also unlikely to be a consequence of gestational markers of inflammation (i.e. they are unlikely to be mediators), and consequently controlling for them is not expected to change the conclusion of this study. Finally, it is unknown whether any mothers had an infection at the time of inflammatory marker collection or whether mothers were taking any medication that may have influenced inflammatory marker concentrations.

In conclusion, this study did not find evidence of an association between gestational inflammatory markers and adiposity at age 7 or 13 years. However, several potential sex differences were identified that should be further confirmed in future studies.

Supplementary Material

Supplemental Material

Table 2.

Summary of child adiposity markers measured at age 7 years.

Overall Males Females
7 years (n=1,359) 13 years (n=1,273) 7 years (n=704) 13 years (n=664) 7 years (n=654) 13 years (n=609)
Age at measurement, Median (Range) 7.3 (7.0, 7.9) 13.6 (12.5, 14.9) 7.3 (7.0, 7.8) 13.6 (12.5, 14.9) 7.3 (7.0, 7.9) 13.5 (12.6, 14.8)
BMI-for-age z-score1, Median (SD) 0.28 (1.55) 0.01 (1.69) 0.35 (1.41) −0.05 (1.77) 0.21 (1.41) 0.07 (1.6)
Thinness, N (%) 55 (4.1%) 134 (10.5%) 33 (4.8%) 86 (13.0%) 22 (3.4%) 48 (7.9%)
Normal weight, N (%) 927 (68.8%) 766 (60.3%) 469 (67.6%) 382 (57.5%) 458 (70.1%) 384 (63.3%)
Overweight, N (%) 199 (14.8%) 181 (14.2%) 93 (13.4%) 87 (13.1%) 106 (16.2%) 94 (15.5%)
Obesity, N (%) 166 (12.3%) 190 (15.0%) 99 (14.3%) 109 (16.4%) 67 (10.3%) 81 (13.3%)
Missing 55 125 31 61 16 59
Waist-to-Hip ratio, Median (SD) 0.87 (0.06) 0.82 (0.06) 0.88 (0.06) 0.85 (0.06) 0.87 (0.05) 0.80 (0.06)
Missing 45 123 22 61 18 57
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1

Child BMI categorization based on the number of standard deviations away from the population mean (de Onis et al., 2007): underweight (2 or more SDs below the mean), overweight (more than 1 SD above the mean), obesity (2 or more SDs above the mean). BMI-for-age z-scores less than −5 or greater than 5 are considered implausible (de Onis et al., 2007). Mean (SD) and median (min, max) do not include children with implausible values.

Significance.

Disruptions in the maternal cytokine milieu during pregnancy can influence fetal metabolic programming and increase the offspring’s risk of obesity. Previous epidemiologic studies have reported varying directions of association between maternal inflammatory biomarkers and childhood adiposity. Few of these studies measured waist circumference in children and none measured hip circumference. We utilized a large, prospective cohort study with a large panel of maternal inflammatory biomarkers and child adiposity measured using BMI-for-age z-scores, categorical weight status, and waist-to-hip circumference. We did not observe an association between second trimester maternal inflammatory biomarkers and adiposity in this cohort.

Acknowledgements:

This research was supported by grants R01-ES010219 and P30-ES01247 from the United States National Institute of Environmental Health Sciences (National Institutes of Health) and in-kind by the Government of the Republic of Seychelles. We acknowledge with thanks the contribution of the nursing and laboratory teams in Seychelles. The study sponsors had no role in the design, collection, analysis, or interpretation of the data; in the writing of the report; or in the decision to submit the article for publication.

Declarations:

No authors have any competing interests to report. This research was supported by grants R01-ES010219, R24-ES029466, and P30-ES01247 from the United States National Institute of Environmental Health Sciences (National Institutes of Health) and in-kind by the Government of the Republic of Seychelles

Data availability:

Data and code used in these analyses may be provided upon reasonable request and IRB approval.

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Associated Data

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

Supplementary Materials

Supplemental Material
NIHMS2179011-supplement-Supplemental_Material.pdf (1.2MB, pdf)

Data Availability Statement

Data and code used in these analyses may be provided upon reasonable request and IRB approval.

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