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Cited 31 time in webofscience Cited 32 time in scopus
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Association of urinary phthalate metabolites and phenolics with adipokines and insulin resistance related markers among women of reproductive age

Authors
Lee, InaeKim, SunmiPark, SuhyeonMok, SoriJeong, YunsunMoon, Hyo-BangLee, JangwooKim, SungkyoonKim, Hai-JoongChoi, GyuyeonChoi, SooranKim, Su YoungLee, AramPark, JeongimChoi, Kyungho
Issue Date
Oct-2019
Publisher
Elsevier BV
Keywords
Phthalate; Phenolic; Adiponectin; Glucose; Insulin resistance
Citation
Science of the Total Environment, v.688, pp 1319 - 1326
Pages
8
Indexed
SCI
SCIE
SCOPUS
Journal Title
Science of the Total Environment
Volume
688
Start Page
1319
End Page
1326
URI
https://scholarworks.korea.ac.kr/kumedicine/handle/2020.sw.kumedicine/1511
DOI
10.1016/j.scitotenv.2019.06.125
ISSN
0048-9697
1879-1026
Abstract
Chemicals such as phthalates and phenolics have been associated with metabolic markers in humans. However, most studies have only looked at a limited number of chemicals, and little is known about their potential effects on adipokines in humans. In the present study, the associations between dozens of urinary chemicals, including phthalate metabolites and phenolics, and markers related to insulin resistance as well as major adipokines, were assessed among the women of reproductive age (n = 459, between 20 and 48 years of age) recruited from major cities in Korea between 2015 and 2016. Adipokines such as adiponectin and leptin, and insulin resistance related markers such as glucose and insulin, were analyzed in serum. Associations between urinary chemicals and the adipokines or insulin resistance related markers were assessed in two steps. First, ordinary least squares (OLS) regression was used to assess the association of each urinary chemical with the adipokines or insulin resistance related markers (single-pollutant model). Second, several chemicals were selected using elastic net regression and were subsequently analyzed with OLS regression model (multi-pollutant model), considering simultaneous exposure to multiple chemicals. In both single- and multi-pollutant models, several urinary chemicals consistently showed significant associations with adipokines or the insulin resistance related markers. The sum of di-(2-ethylhexyl) phthalate metabolites (Sigma DEHPm) and ethyl paraben (EtP) were associated with increased serum adiponectin levels. Urinary Sigma DEHPm levels also showed positive associations with fasting glucose. Moreover, urinary mono-methyl phthalate (MMP), mono-isobutyl phthalate (MiBP), and bisphenol S (BPS) levels showed positive associations with the homeostasis model assessment for insulin resistance (HOMA-IR). Interestingly, urinary propyl paraben (PrP) levels showed a negative association with HOMA-IR, in both models. Our observations show that among many consumer chemicals, phthalates may affect serum adipokines, and thus glucose, and insulin resistance in adult females. Further confirmation is warranted in other populations.
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