Evidence map›Paper›PMID 34004451›Full record

ArticleEnvironment international2021

Urinary phthalate metabolite concentrations and serum hormone levels in pre- and perimenopausal women from the Midlife Women's Health Study.

Catheryne Chiang, Diana C Pacyga, Rita S Strakovsky, Rebecca L Smith, Tamarra James-Todd, Paige L Williams, Russ Hauser, Daryl D Meling, Zhong Li, Jodi A Flaws

Open access · goldAbstract read
In one paragraph

Article in Environment international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
2.7field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 38 citations in OpenAlex.

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  6. Single-cell RNA-seq reveals that granulosa cells are a target of phthalate toxicity in the ovary.Toxicological sciences : an official journal of the Society of Toxicology · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 1 country.

Catheryne ChiangDepartment of Comparative Biosciences, University of Illinois, Urbana, IL 61802, United States.
Diana C PacygaDepartment of Food Science and Human Nutrition, Michigan State University, East Lansing, MI 48823, United States; Institute for Integrative Toxicology, Michigan State University, East Lansing, MI 48823, United States; Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI 48823, United States.
Rita S StrakovskyDepartment of Food Science and Human Nutrition, Michigan State University, East Lansing, MI 48823, United States; Institute for Integrative Toxicology, Michigan State University, East Lansing, MI 48823, United States.
Rebecca L SmithInstitute for Genomic Biology, University of Illinois, Urbana, IL 61801, United States; Department of Pathobiology, University of Illinois, Urbana, IL 61802, United States.
Tamarra James-ToddDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States; Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States.
Paige L WilliamsDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States.
Russ HauserDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States; Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States.
Daryl D MelingDepartment of Comparative Biosciences, University of Illinois, Urbana, IL 61802, United States.
Zhong LiRoy J. Carver Biotechnology Center, University of Illinois, Urbana, IL 61801, United States.
Jodi A FlawsDepartment of Comparative Biosciences, University of Illinois, Urbana, IL 61802, United States; Institute for Genomic Biology, University of Illinois, Urbana, IL 61801, United States. Electronic address: jflaws@illinois.edu.
University of Illinois Urbana-Champaign · USHarvard University · USMichigan State University · US

Funding

Research Training Program in Toxicology and Environmental HealthT32ES007326 · NIEHS · UNIVERSITY OF ILLINOIS URBANA-CHAMPAIGN · PI Jodi A. Flaws · 2000 to 2026
$8.7M
Testosterone-GnRH Frequency and the Evolution of PCOS in AdolescenceP50HD028934 · NICHD · UNIVERSITY OF VIRGINIA · PI HAISENLEDER, DANIEL J. · 2014 to 2018
$8.6M
Phthalate exposure and hot flashes in midlife womenR01ES026956 · NIEHS · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI FLAWS, JODI A. · 2017 to 2020
$1.7M
NICHD NIH HHS P50 HD028934NIEHS NIH HHS R01 ES026956NIEHS NIH HHS T32 ES007326
6 · The paper itself

Abstract

backgroundPhthalate exposure is associated with altered reproductive function, but little is known about associations between phthalate and hormone levels in midlife women.

methodsThis cross-sectional analysis includes 45-54-year-old pre- and perimenopausal women from Baltimore, MD and its surrounding counties enrolled in the Midlife Women's Health Study (n = 718). Serum and urine samples were collected from participants once a week for four consecutive weeks to span the menstrual cycle. Serum samples were assayed for estradiol, testosterone, progesterone, sex hormone binding globulin (SHBG), follicle-stimulating hormone (FSH), and anti-Müllerian hormone (AMH), and geometric means were calculated for each hormone across all four weeks. Urine samples were analyzed for nine phthalate metabolites from pools of one-to-four urine samples. Phthalate metabolite concentrations were specific gravity-adjusted and assessed as individual metabolites or as molar sums of metabolites from common parents (di(2-ethylhexyl) phthalate metabolites, ∑DEHP), exposure sources (plastic, ∑Plastics; personal care products, ∑PCP), biological activity (anti-androgenic, ∑AA), and sum of all metabolites (∑Phthalates). We used linear regression models to assess overall associations of phthalate metabolites with hormones, controlling for important demographic, lifestyle, and health factors. We also explored whether associations differed by menopause status, body mass index (BMI), and race/ethnicity.

resultsMost participants were non-Hispanic white (67%) or black (29%), college-educated (65%), employed (80%), and had somewhat higher mean urinary phthalate metabolite concentrations than other U.S. women. Overall, the following positive associations were observed between phthalate metabolites and hormones: ∑DEHP (%Δ: 4.9; 95%CI: 0.5, 9.6), ∑Plastics (%Δ: 5.1; 95%CI: 0.3, 10.0), and ∑AA (%Δ: 7.8; 95%CI: 2.3, 13.6) with estradiol; MiBP (%Δ: 6.6; 95%CI: 1.5, 12.1) with testosterone; ∑DEHP (%Δ: 8.3; 95%CI: 1.5, 15.6), ∑Plastics (%Δ: 9.8; 95%CI: 2.4, 17.7), MEP (%Δ: 4.6; 95%CI: 0.1, 9.2), ∑PCP (%Δ: 6.0; 95%CI: 0.2, 12.2), ∑Phthalates (%Δ: 9.0; 95%CI: 2.1, 16.5), and ∑AA (%Δ: 12.9; 95%CI: 4.4, 22.1) with progesterone; and MBP (%Δ: 8.5; 95%CI: 1.2, 16.3) and ∑AA (%Δ: 9.0; 95%CI: 1.3, 17.4) with AMH. Associations of phthalate metabolites with hormones differed by menopause status (strongest in premenopausal women for estradiol, progesterone, and FSH), BMI (strongest in obese women for progesterone), and race/ethnicity (strongest in non-Hispanic white women for estradiol and AMH).

conclusionsWe found that phthalate metabolites were positively associated with several hormones in midlife women, and that some demographic and lifestyle characteristics modified these associations. Future longitudinal studies are needed to corroborate these findings in more diverse midlife populations.

Indexed as

PerimenopausePhthalic AcidsCross-Sectional StudiesFemaleHumansMiddle AgedTestosteroneWomen's Healthphthalic acidPhthalic AcidsTestosteroneHormonesMid-life womenPhthalates

Identifiers

PMID34004451
PMCPMC8380691
OpenAlexW3160925421

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.