Evidence map›Paper›PMID 31103473›Full record

ArticleInternational journal of hygiene and environmental health2019

Urinary metals and metal mixtures in midlife women: The Study of Women's Health Across the Nation (SWAN).

Xin Wang, Bhramar Mukherjee, Stuart Batterman, Siobán D Harlow, Sung Kyun Park

Open access · greenAbstract read
In one paragraph

Article in International journal of hygiene and environmental health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
2.9field-weighted citation impact, top 9% 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

31 citing papers in PubMed, 46 citations in OpenAlex.

  1. Article
  2. Exposure to Cadmium and Cerebrovascular Mortality in the United States.Hygiene and environmental health advances · 2025
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  7. Heavy Metals and Trajectories of Anti-Müllerian Hormone During the Menopausal Transition.The Journal of clinical endocrinology and metabolism · 2024
    Article
  8. Article
  9. The MAK collection for occupational health and safety · 2024
    Review
  10. Review
  11. Article
  12. Correlates of whole blood metal concentrations among reproductive-aged Black women.Journal of exposure science & environmental epidemiology · 2023
    Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
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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

5 authors at 1 institution in 1 country.

Xin WangDepartment of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA.
Bhramar MukherjeeDepartment of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, USA.
Stuart BattermanDepartment of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA.
Siobán D HarlowDepartment of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA.
Sung Kyun ParkDepartment of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA; Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA. Electronic address: sungkyun@umich.edu.
University of Michigan–Ann Arbor · US

Funding

UCSF CLINICAL AND TRANSLATIONAL SCIENCE INSTITUTEUL1RR024131 · NCRR · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI JOHNSTON, S. CLAIBORNE · 2006 to 2011
$111.2M
WOMENS HEALTH ACROSS THE NATION--COORDINATING CENTERU01AG012553 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BROOKS, MARIA MORI · 1994 to 2019
$37.7M
University of Michigan ERC-supplement (TRT)T42OH008455 · OH · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI NEITZEL, RICHARD L · 2005 to 2025
$32.3M
SWAN Repository IVU01AG017719 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI HARLOW, SIOBAN D · 2000 to 2020
$25.0M
Strategic Vision & Impact on Environmental HealthP30ES017885 · NIEHS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Dana Dolinoy · 2011 to 2026
$21.3M
WOMENS HEALTH ACROSS THE NATION--ENDOCRINE LABU01AG012495 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MCCONNELL, DANIEL S · 1994 to 2018
$18.8M
WOMENS HEALTH ACROSS THE NATION--PITTSBURGHU01AG012546 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI MATTHEWS, KAREN · 1994 to 2019
$16.2M
WOMENS HEALTH ACROSS THE NATION--UCDAVISU01AG012554 · NIA · UNIVERSITY OF CALIFORNIA DAVIS · PI GOLD, ELLEN B. · 1994 to 2019
$14.5M
WOMENS HEALTH ACROSS THE NATION--UCLAU01AG012539 · NIA · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI GREENDALE, GAIL A · 1994 to 2018
$13.7M
THE STUDY OF WOMEN'S HEALTH ACROSS THE NATION-MICHIGANU01NR004061 · NINR · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI HARLOW, SIOBAN D · 1994 to 2018
$12.9M
WOMENS HEALTH ACROSS THE NATION--CHICAGOU01AG012505 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI KRAVITZ, HOWARD M · 1994 to 2019
$11.9M
WOMENS HEALTH ACROSS THE NATION--MASSACHUSETTS GENERAL HU01AG012531 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI FINKELSTEIN, JOEL S · 1994 to 2019
$10.7M
NCRR NIH HHS UL1 RR024131NIA NIH HHS U01 AG012495NIA NIH HHS U01 AG012505NIA NIH HHS U01 AG012531NIA NIH HHS U01 AG012535NIA NIH HHS U01 AG012539NIA NIH HHS U01 AG012546NIA NIH HHS U01 AG012553NIA NIH HHS U01 AG012554NIA NIH HHS U01 AG017719NIEHS NIH HHS P30 ES017885NIEHS NIH HHS R01 ES026578NIEHS NIH HHS R01 ES026964NINR NIH HHS U01 NR004061NIOSH CDC HHS T42 OH008455
6 · The paper itself

Abstract

backgroundLittle is known about the extent of exposure to metals and metal mixtures among midlife women.

objectivesWe assessed exposure to multiple metals in the Study of Women's Health Across the Nation (SWAN), a multi-site, multi-racial/ethnic cohort of women at midlife.

methodsWe measured urinary concentrations of 21 metals (arsenic, barium, beryllium, cadmium, cobalt, chromium, cesium, copper, mercury, manganese, molybdenum, nickel, lead, platinum, antimony, tin, thallium, uranium, vanadium, tungsten and zinc) using high-resolution inductively coupled plasma-mass spectrometry among 1335 white, black, Chinese and Japanese women aged 45-56 years at the third SWAN annual visit (1999-2000). Least squared geometric mean concentrations were compared across race/ethnicity, education, financial hardship, smoking, secondhand smoking, seafood intake and rice intake groups. Overall exposure patterns of multiple metals were derived using k-means clustering method.

resultsThe percentage of women with detectable concentrations of metals ranged from 100% for arsenic, cesium, molybdenum and zinc, to less than 5% for platinum; 15 metals had detection rates of 70% or more. Asian women, both Chinese and Japanese, had higher urinary concentrations of arsenic, cadmium, copper, mercury, molybdenum, lead and thallium, compared with other race/ethnic groups, independent of sociodemographic, lifestyle, dietary, and geographic characteristics. Seafood and rice intake were important determinants of urinary arsenic, cesium, mercury, molybdenum and lead levels. Two distinct overall exposure patterns- "high" vs. "low" -- were identified. Women in the "high" overall exposure pattern were more likely to be Asians, current smokers, and to report high consumption of seafood and rice. Black women were less likely to have the high exposure pattern.

conclusionsMetal exposure of midlife women differs by racial/ethnic, sociodemographic, lifestyle, dietary, and geographic characteristics. Asian women may be experiencing the highest exposures to multiple metals compared with other racial/ethnic groups in the United States.

Indexed as

Asian PeopleBlack or African AmericanCluster AnalysisCohort StudiesDietEnvironmental ExposureEthnicityFemaleHumansMass SpectrometryMetalsMiddle AgedSocioeconomic FactorsUnited StatesWhite PeopleMetalsClustering analysisMetalsMid-lifeMixturesWomen

Identifiers

PMID31103473
PMCPMC6583796
OpenAlexW2945475715

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.