<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"
	xmlns:content="http://purl.org/rss/1.0/modules/content/"
	xmlns:wfw="http://wellformedweb.org/CommentAPI/"
	xmlns:dc="http://purl.org/dc/elements/1.1/"
	xmlns:atom="http://www.w3.org/2005/Atom"
	xmlns:sy="http://purl.org/rss/1.0/modules/syndication/"
	xmlns:slash="http://purl.org/rss/1.0/modules/slash/"
	>

<channel>
	<title>BWQS &#8211; Science</title>
	<atom:link href="https://scienmag.com/tag/bwqs/feed/" rel="self" type="application/rss+xml" />
	<link>https://scienmag.com</link>
	<description></description>
	<lastBuildDate>Sat, 10 Oct 2026 14:03:27 +0000</lastBuildDate>
	<language>en-US</language>
	<sy:updatePeriod>
	hourly	</sy:updatePeriod>
	<sy:updateFrequency>
	1	</sy:updateFrequency>
	<generator>https://wordpress.org/?v=7.1.3</generator>

<image>
	<url>https://scienmag.com/wp-content/uploads/2024/07/cropped-scienmag_ico-32x32.jpg</url>
	<title>BWQS &#8211; Science</title>
	<link>https://scienmag.com</link>
	<width>32</width>
	<height>32</height>
</image> 
<site xmlns="com-wordpress:feed-additions:1">73899611</site>	<item>
		<title>Pregnancy Chemical Mixtures Show No Clear Link to Early Childhood BMI in Landmark ECHO Study</title>
		<link>https://scienmag.com/pregnancy-chemical-mixtures-show-no-clear-link-to-early-childhood-bmi-in-landmark-echo-study/</link>
		
		<dc:creator><![CDATA[Harold Sullivan]]></dc:creator>
		<pubDate>Sat, 10 Oct 2026 14:03:27 +0000</pubDate>
				<category><![CDATA[Technology and Engineering]]></category>
		<category><![CDATA[biomonitoring]]></category>
		<category><![CDATA[biomonitoring of chemicals in pregnant women]]></category>
		<category><![CDATA[BKMR]]></category>
		<category><![CDATA[BMI z-score]]></category>
		<category><![CDATA[BWQS]]></category>
		<category><![CDATA[chemical mixtures]]></category>
		<category><![CDATA[Childhood obesity]]></category>
		<category><![CDATA[comprehensive analysis of chemical exposure during pregnancy]]></category>
		<category><![CDATA[developmental programming]]></category>
		<category><![CDATA[ECHO program]]></category>
		<category><![CDATA[ECHO study on prenatal chemical mixtures]]></category>
		<category><![CDATA[Endocrine disrupting chemicals]]></category>
		<category><![CDATA[endocrine-disrupting chemicals and childhood BMI]]></category>
		<category><![CDATA[impact of phthalates and phenols during pregnancy]]></category>
		<category><![CDATA[implications of ECHO study findings on public]]></category>
		<category><![CDATA[influence of plastics and personal care products on fetal health]]></category>
		<category><![CDATA[maternal chemical exposure and child health outcomes]]></category>
		<category><![CDATA[non-persistent chemicals and early childhood development]]></category>
		<category><![CDATA[obesogens and childhood obesity risk]]></category>
		<category><![CDATA[phenols]]></category>
		<category><![CDATA[phthalates]]></category>
		<category><![CDATA[prenatal chemical exposure]]></category>
		<category><![CDATA[prenatal exposure]]></category>
		<category><![CDATA[sex-specific effects of environmental chemicals]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=258858</guid>

					<description><![CDATA[A major ECHO Program analysis of 586 mother-child pairs found no significant association between prenatal exposure to a 23-chemical mixture of phenols and phthalates and early childhood BMI, though individual compounds showed non-linear and sex-specific patterns.]]></description>
										<content:encoded><![CDATA[<p>One of the most comprehensive investigations yet into whether chemicals encountered during pregnancy shape a child&#8217;s body weight has delivered a nuanced and, in part, reassuring verdict. A team of researchers working within the U.S. Environmental influences on Child Health Outcomes (ECHO) Program examined prenatal exposure to 23 endocrine-disrupting chemicals—ten phenols and thirteen phthalate metabolites—and their relationship to body mass index in early childhood. Their findings, published in Pediatric Research, reveal no statistically significant association between the overall chemical mixture and childhood BMI, even as individual compounds displayed intriguing, non-linear and sex-specific patterns that keep the debate about so-called obesogens very much alive.</p>
<p>The chemicals in question are ubiquitous in modern life. Phthalates, which make plastics flexible, appear in food packaging, pharmaceuticals, dietary supplements, and personal care products. Phenols, including bisphenol A, bisphenol S, parabens, benzophenone-3, and triclosan, are found in everything from water bottles and receipt paper to cosmetics and antibacterial soaps. Because these substances are metabolized and excreted within hours to days, they are classified as non-persistent, yet the near-constant stream of exposure means biomonitoring studies routinely detect them in more than 90 percent of pregnant women in the United States. That combination of ubiquity and biological transience is precisely what makes studying their health effects so challenging.</p>
<p>The scientific rationale for concern is grounded in developmental biology. During embryonic and fetal development, organogenesis and tissue differentiation are exquisitely sensitive to hormonal signals, and endocrine-disrupting chemicals can interfere with the hormonal regulation of metabolism and energy balance. Phthalates, for example, can activate nuclear hormone receptors, particularly peroxisome proliferator-activated receptors, which govern adipogenesis, lipid metabolism, and energy storage. Activation of PPAR-gamma in the developing fetus may promote adipocyte differentiation and alter the production of adipokines such as leptin and adiponectin, potentially predisposing offspring to altered adiposity trajectories after birth. Some phthalates also exhibit anti-androgenic and weakly estrogenic activity, disrupting hormone signaling in utero, and previous research has linked prenatal phthalate exposure to altered steroid hormone profiles in humans as well as adverse metabolic outcomes in animal models.</p>
<p>To interrogate these questions at scale, the research team, led by Dorothy Nakiwala of the University of Colorado Anschutz Medical Campus, drew on 586 mother-child pairs from three ECHO cohort sites: the PROTECT Study in Puerto Rico, which recruited between 2010 and 2018; the Healthy Start Study in Colorado, recruited from 2009 to 2014; and the Illinois Kids Development Study, recruited from 2013 to 2018. All births occurred between 2009 and 2020. Maternal urine samples collected during pregnancy were shipped frozen to the Centers for Disease Control and Prevention, where concentrations of the phenol and phthalate metabolites were quantified using established laboratory methods. Children&#8217;s weight and height were measured primarily during clinic visits, and body mass index was converted to sex- and age-specific z-scores using the CDC 2000 growth charts, with assessments occurring between ages two and five at a mean age of 3.96 years.</p>
<p>The methodological architecture of the study is where it distinguishes itself from much of the prior literature. Rather than relying on a single statistical approach, the researchers triangulated their findings using covariate-adjusted single-pollutant linear regression alongside two complementary mixture methods: Bayesian Weighted Quantile Sum regression and Bayesian Kernel Machine Regression. The BWQS approach collapses multiple correlated exposures into a single weighted index under the assumption of a monotonic dose-response relationship, while BKMR uses a kernel function to flexibly model non-linear and interactive exposure-response patterns without imposing such assumptions. Models were adjusted for child sex and age, maternal age at delivery, pre-pregnancy BMI, parity, maternal race, maternal education, and study site, with covariate selection guided by a directed acyclic graph. Exposures were modeled both as continuous, log-transformed variables and as tertile categories to allow detection of threshold effects.</p>
<p>The headline result was null. When the entire 23-chemical mixture was evaluated, neither BWQS nor BKMR identified a statistically significant association with childhood BMI z-scores. The BWQS posterior mean estimate for a one-tertile increase in the mixture index was −0.06, with a credible interval spanning zero, and sex-stratified estimates of −0.24 for boys and 0.03 for girls were similarly inconclusive. The BKMR overall risk function, comparing joint increases in all exposures from the 25th to the 75th percentile against the 25th percentile, showed a non-significant, non-linear relationship with wide uncertainty intervals. There was also no evidence of interactions among pollutants, meaning the effect of any single chemical did not change appreciably as levels of the others rose.</p>
<p>The single-pollutant analyses, however, told a subtler story. When exposures were treated as continuous variables, no significant associations emerged. But when chemicals were categorized into tertiles, non-monotonic patterns appeared. Mono-benzyl phthalate, a metabolite of benzyl butyl phthalate, showed an inverse association: children whose mothers fell in the highest exposure tertile had BMI z-scores 0.33 lower than those in the lowest tertile, with a 95 percent confidence interval of −0.60 to −0.06. Mono-ethyl phthalate, a metabolite of diethyl phthalate, showed the opposite tendency, with the second tertile associated with a BMI z-score 0.27 higher than the first. Most strikingly, among boys only, mono-n-butyl phthalate in the second tertile was associated with a BMI z-score 0.45 higher than the first tertile, a non-monotonic pattern in which the third tertile showed no significant elevation. Among girls, the mono-ethyl phthalate pattern mirrored the pooled results but did not reach statistical significance.</p>
<p>The researchers are careful to contextualize these effect sizes. A shift of 0.1 to 0.2 standard deviations in BMI z-score may not be clinically meaningful for an individual child, but at the population level, even modest average shifts can increase the proportion of children classified as overweight or obese. Given that prenatal exposure to phenols and phthalates is essentially universal, small average effects could translate into a meaningful public health burden. The inverse association with mono-benzyl phthalate, meanwhile, aligns with at least one prior study, and one hypothesis holds that certain phthalates may impair growth by selectively disrupting muscle development rather than promoting fat accumulation, which could explain why phthalate exposure sometimes correlates with lower rather than higher BMI. The positive associations with mono-ethyl phthalate and mono-n-butyl phthalate, both low molecular weight phthalates found in pharmaceuticals, supplements, and personal care products, echo earlier reports linking prenatal mono-ethyl phthalate exposure to higher BMI trajectories from ages two to fourteen.</p>
<p>The consistency of the null mixture findings with previous research is itself informative. Studies using BKMR by Güil-Oumrait and colleagues, Berger and colleagues, and Ouidir and colleagues similarly reported no significant associations between prenatal phenol-phthalate mixtures and BMI z-scores at ages ten, five, and three, respectively, while cumulative-exposure studies using weighted quantile sum approaches by Svensson and Montazeri and their teams also found null results. One plausible explanation lies in exposure misclassification: because these chemicals clear the body so rapidly, spot urine samples may not adequately represent exposure across an entire pregnancy, and random misclassification typically biases results toward the null. The authors also note that BMI, their primary outcome, reflects overall body size without distinguishing fat from lean mass, potentially masking specific adiposity pathways, and that residual confounding by dietary behaviors associated with packaged and processed food consumption cannot be excluded.</p>
<p>Looking forward, the study&#8217;s authors argue that future research should prioritize repeated biomonitoring throughout pregnancy to better characterize exposures that fluctuate substantially over time, along with adequate statistical power to evaluate sex-specific effects, longitudinal follow-up, and direct measures of body composition. They also emphasize that postnatal and concurrent childhood exposures deserve attention, particularly given the short biological half-lives of these compounds. For now, the message is one of calibrated caution: the strongest evidence to date finds no cumulative effect of prenatal phenol-phthalate mixtures on early childhood BMI, but suggestive non-monotonic and sex-specific signals for individual chemicals underscore that the obesogen hypothesis, and the chemistry of everyday products that underpins it, remains a question science has not yet closed.</p>
<p><strong>Subject of Research:</strong> Prenatal exposure to endocrine-disrupting phenols and phthalates and early childhood body mass index</p>
<p><strong>Article Title:</strong> Prenatal exposure to nonpersistent endocrine disruptors and early childhood BMI: single pollutant and mixture analyses from the ECHO Program</p>
<p><strong>Article References:</strong> Nakiwala, D., Perng, W., Barrett, E. S., Niu, Z., Alshawabkeh, A. N., Meeker, J. D., Dabelea, D., Starling, A. P., for the ECHO Cohort Consortium, Smith, P. B., Newby, L. K., Adair, L., Jacobson, L. P., Catellier, D., McGrath, M., Douglas, C., Duggal, P., Knapp, E., Kress, A., &#8230; Smith, L. M. (2026). Prenatal exposure to nonpersistent endocrine disruptors and early childhood BMI: single pollutant and mixture analyses from the ECHO Program. <em>Pediatric Research</em>. <a href="https://doi.org/10.1038/s41390-026-05466-7" rel="noopener noreferrer">https://doi.org/10.1038/s41390-026-05466-7</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1038/s41390-026-05466-7" rel="noopener noreferrer">10.1038/s41390-026-05466-7</a></p>
<p><strong>Keywords:</strong> endocrine-disrupting chemicals, phthalates, phenols, prenatal exposure, childhood obesity, BMI z-score, ECHO Program, chemical mixtures, BKMR, BWQS, developmental programming, biomonitoring</p>
]]></content:encoded>
					
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">258858</post-id>	</item>
	</channel>
</rss>
