Predictors of urinary polycyclic aromatic hydrocarbon metabolites in girls from the San Francisco Bay Area

Background: Polycyclic aromatic hydrocarbon (PAH) exposures from tobacco smoke, automobile exhaust, grilled or smoked meat and other sources are widespread and are a public health concern, as many are classified as probable carcinogens and suspected endocrine-disrupting chemicals. PAH exposures can be quantified using urinary biomarkers.Methods: Seven urinary metabolites of naphthalene, fluorene, phenanthrene, and pyrene were measured in two samples collected from girls aged 6–16 years from the San Francisco Bay Area. We used Spearman correlation coefficients (SCC) to assess correlations among metabolite concentrations (corrected for specific gravity) separately in first (n = 359) and last (N = 349) samples, and to assess consistency of measurements in samples collected up to 72 months apart. Using multivariable linear regression, we assessed variation in mean metabolites across categories of participant characteristics and potential outdoor, indoor, and dietary sources of PAH exposures.Results: The detection rate of PAH metabolites was high (4 metabolites in ≥98% of first samples; 5 metabolites in ≥95% of last samples). Correlations were moderate to strong between fluorene, phenanthrene and pyrene metabolites (SCC 0.43–0.82), but weaker between naphthalene and the other metabolites (SCC 0.18–0.36). SCC between metabolites in first and last samples ranged from 0.15 to 0.49. When classifying metabolite concentrations into tertiles based on single samples (first or last samples) vs. the average of the two samples, agreement was moderate to substantial (weighted kappa statistics 0.52–0.65). For specific metabolites, concentrations varied by age, race/ethnicity, and body mass index percentile, as well as by outdoor sources (season of sample collection, street traffic), indoor sources (heating with gas, cigarette smoke), and dietary sources (frequent use of grill, consumption of smoked meat or fish) of PAH exposures.Conclusions: Urinary PAH exposure was widespread in girls aged 6–16 years and associated with several sources of exposure. Tertile classification of a single urine sample provides reliable PAH exposure ranking. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	John, Esther M. [verfasserIn] Koo, Jocelyn [verfasserIn] Ingles, Sue A. [verfasserIn] Keegan, Theresa H. [verfasserIn] Nguyen, Jenny T. [verfasserIn] Thomsen, Catherine [verfasserIn] Terry, Mary Beth [verfasserIn] Santella, Regina M. [verfasserIn] Nguyen, Khue [verfasserIn] Yan, Beizhan [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	Biomarkers Children Epidemiology Polycyclic aromatic hydrocarbons (PAHs) Urinary metabolites

Übergeordnetes Werk:	Enthalten in: Environmental research - San Diego, Calif. : Elsevier, 1967, 205
Übergeordnetes Werk:	volume:205

DOI / URN:	10.1016/j.envres.2021.112534

Katalog-ID:	ELV007244614

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024	7		\|a 10.1016/j.envres.2021.112534 \|2 doi
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100	1		\|a John, Esther M. \|e verfasserin \|0 (orcid)0000-0003-3259-8003 \|4 aut
245	1	0	\|a Predictors of urinary polycyclic aromatic hydrocarbon metabolites in girls from the San Francisco Bay Area
264		1	\|c 2021
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337			\|a Computermedien \|b c \|2 rdamedia
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520			\|a Background: Polycyclic aromatic hydrocarbon (PAH) exposures from tobacco smoke, automobile exhaust, grilled or smoked meat and other sources are widespread and are a public health concern, as many are classified as probable carcinogens and suspected endocrine-disrupting chemicals. PAH exposures can be quantified using urinary biomarkers.Methods: Seven urinary metabolites of naphthalene, fluorene, phenanthrene, and pyrene were measured in two samples collected from girls aged 6–16 years from the San Francisco Bay Area. We used Spearman correlation coefficients (SCC) to assess correlations among metabolite concentrations (corrected for specific gravity) separately in first (n = 359) and last (N = 349) samples, and to assess consistency of measurements in samples collected up to 72 months apart. Using multivariable linear regression, we assessed variation in mean metabolites across categories of participant characteristics and potential outdoor, indoor, and dietary sources of PAH exposures.Results: The detection rate of PAH metabolites was high (4 metabolites in ≥98% of first samples; 5 metabolites in ≥95% of last samples). Correlations were moderate to strong between fluorene, phenanthrene and pyrene metabolites (SCC 0.43–0.82), but weaker between naphthalene and the other metabolites (SCC 0.18–0.36). SCC between metabolites in first and last samples ranged from 0.15 to 0.49. When classifying metabolite concentrations into tertiles based on single samples (first or last samples) vs. the average of the two samples, agreement was moderate to substantial (weighted kappa statistics 0.52–0.65). For specific metabolites, concentrations varied by age, race/ethnicity, and body mass index percentile, as well as by outdoor sources (season of sample collection, street traffic), indoor sources (heating with gas, cigarette smoke), and dietary sources (frequent use of grill, consumption of smoked meat or fish) of PAH exposures.Conclusions: Urinary PAH exposure was widespread in girls aged 6–16 years and associated with several sources of exposure. Tertile classification of a single urine sample provides reliable PAH exposure ranking.
650		4	\|a Biomarkers
650		4	\|a Children
650		4	\|a Epidemiology
650		4	\|a Polycyclic aromatic hydrocarbons (PAHs)
650		4	\|a Urinary metabolites
700	1		\|a Koo, Jocelyn \|e verfasserin \|4 aut
700	1		\|a Ingles, Sue A. \|e verfasserin \|4 aut
700	1		\|a Keegan, Theresa H. \|e verfasserin \|0 (orcid)0000-0002-1961-4008 \|4 aut
700	1		\|a Nguyen, Jenny T. \|e verfasserin \|4 aut
700	1		\|a Thomsen, Catherine \|e verfasserin \|4 aut
700	1		\|a Terry, Mary Beth \|e verfasserin \|4 aut
700	1		\|a Santella, Regina M. \|e verfasserin \|0 (orcid)0000-0003-0823-6221 \|4 aut
700	1		\|a Nguyen, Khue \|e verfasserin \|4 aut
700	1		\|a Yan, Beizhan \|e verfasserin \|4 aut
773	0	8	\|i Enthalten in \|t Environmental research \|d San Diego, Calif. : Elsevier, 1967 \|g 205 \|h Online-Ressource \|w (DE-627)266876927 \|w (DE-600)1467489-0 \|w (DE-576)109967119 \|x 1096-0953 \|7 nnns
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936	b	k	\|a 44.13 \|j Medizinische Ökologie \|q VZ
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allfields	10.1016/j.envres.2021.112534 doi (DE-627)ELV007244614 (ELSEVIER)S0013-9351(21)01835-1 DE-627 ger DE-627 rda eng 333.7 610 VZ 44.13 bkl John, Esther M. verfasserin (orcid)0000-0003-3259-8003 aut Predictors of urinary polycyclic aromatic hydrocarbon metabolites in girls from the San Francisco Bay Area 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background: Polycyclic aromatic hydrocarbon (PAH) exposures from tobacco smoke, automobile exhaust, grilled or smoked meat and other sources are widespread and are a public health concern, as many are classified as probable carcinogens and suspected endocrine-disrupting chemicals. PAH exposures can be quantified using urinary biomarkers.Methods: Seven urinary metabolites of naphthalene, fluorene, phenanthrene, and pyrene were measured in two samples collected from girls aged 6–16 years from the San Francisco Bay Area. We used Spearman correlation coefficients (SCC) to assess correlations among metabolite concentrations (corrected for specific gravity) separately in first (n = 359) and last (N = 349) samples, and to assess consistency of measurements in samples collected up to 72 months apart. Using multivariable linear regression, we assessed variation in mean metabolites across categories of participant characteristics and potential outdoor, indoor, and dietary sources of PAH exposures.Results: The detection rate of PAH metabolites was high (4 metabolites in ≥98% of first samples; 5 metabolites in ≥95% of last samples). Correlations were moderate to strong between fluorene, phenanthrene and pyrene metabolites (SCC 0.43–0.82), but weaker between naphthalene and the other metabolites (SCC 0.18–0.36). SCC between metabolites in first and last samples ranged from 0.15 to 0.49. When classifying metabolite concentrations into tertiles based on single samples (first or last samples) vs. the average of the two samples, agreement was moderate to substantial (weighted kappa statistics 0.52–0.65). For specific metabolites, concentrations varied by age, race/ethnicity, and body mass index percentile, as well as by outdoor sources (season of sample collection, street traffic), indoor sources (heating with gas, cigarette smoke), and dietary sources (frequent use of grill, consumption of smoked meat or fish) of PAH exposures.Conclusions: Urinary PAH exposure was widespread in girls aged 6–16 years and associated with several sources of exposure. Tertile classification of a single urine sample provides reliable PAH exposure ranking. Biomarkers Children Epidemiology Polycyclic aromatic hydrocarbons (PAHs) Urinary metabolites Koo, Jocelyn verfasserin aut Ingles, Sue A. verfasserin aut Keegan, Theresa H. verfasserin (orcid)0000-0002-1961-4008 aut Nguyen, Jenny T. verfasserin aut Thomsen, Catherine verfasserin aut Terry, Mary Beth verfasserin aut Santella, Regina M. verfasserin (orcid)0000-0003-0823-6221 aut Nguyen, Khue verfasserin aut Yan, Beizhan verfasserin aut Enthalten in Environmental research San Diego, Calif. : Elsevier, 1967 205 Online-Ressource (DE-627)266876927 (DE-600)1467489-0 (DE-576)109967119 1096-0953 nnns volume:205 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 44.13 Medizinische Ökologie VZ AR 205
spelling	10.1016/j.envres.2021.112534 doi (DE-627)ELV007244614 (ELSEVIER)S0013-9351(21)01835-1 DE-627 ger DE-627 rda eng 333.7 610 VZ 44.13 bkl John, Esther M. verfasserin (orcid)0000-0003-3259-8003 aut Predictors of urinary polycyclic aromatic hydrocarbon metabolites in girls from the San Francisco Bay Area 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background: Polycyclic aromatic hydrocarbon (PAH) exposures from tobacco smoke, automobile exhaust, grilled or smoked meat and other sources are widespread and are a public health concern, as many are classified as probable carcinogens and suspected endocrine-disrupting chemicals. PAH exposures can be quantified using urinary biomarkers.Methods: Seven urinary metabolites of naphthalene, fluorene, phenanthrene, and pyrene were measured in two samples collected from girls aged 6–16 years from the San Francisco Bay Area. We used Spearman correlation coefficients (SCC) to assess correlations among metabolite concentrations (corrected for specific gravity) separately in first (n = 359) and last (N = 349) samples, and to assess consistency of measurements in samples collected up to 72 months apart. Using multivariable linear regression, we assessed variation in mean metabolites across categories of participant characteristics and potential outdoor, indoor, and dietary sources of PAH exposures.Results: The detection rate of PAH metabolites was high (4 metabolites in ≥98% of first samples; 5 metabolites in ≥95% of last samples). Correlations were moderate to strong between fluorene, phenanthrene and pyrene metabolites (SCC 0.43–0.82), but weaker between naphthalene and the other metabolites (SCC 0.18–0.36). SCC between metabolites in first and last samples ranged from 0.15 to 0.49. When classifying metabolite concentrations into tertiles based on single samples (first or last samples) vs. the average of the two samples, agreement was moderate to substantial (weighted kappa statistics 0.52–0.65). For specific metabolites, concentrations varied by age, race/ethnicity, and body mass index percentile, as well as by outdoor sources (season of sample collection, street traffic), indoor sources (heating with gas, cigarette smoke), and dietary sources (frequent use of grill, consumption of smoked meat or fish) of PAH exposures.Conclusions: Urinary PAH exposure was widespread in girls aged 6–16 years and associated with several sources of exposure. Tertile classification of a single urine sample provides reliable PAH exposure ranking. Biomarkers Children Epidemiology Polycyclic aromatic hydrocarbons (PAHs) Urinary metabolites Koo, Jocelyn verfasserin aut Ingles, Sue A. verfasserin aut Keegan, Theresa H. verfasserin (orcid)0000-0002-1961-4008 aut Nguyen, Jenny T. verfasserin aut Thomsen, Catherine verfasserin aut Terry, Mary Beth verfasserin aut Santella, Regina M. verfasserin (orcid)0000-0003-0823-6221 aut Nguyen, Khue verfasserin aut Yan, Beizhan verfasserin aut Enthalten in Environmental research San Diego, Calif. : Elsevier, 1967 205 Online-Ressource (DE-627)266876927 (DE-600)1467489-0 (DE-576)109967119 1096-0953 nnns volume:205 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 44.13 Medizinische Ökologie VZ AR 205
allfields_unstemmed	10.1016/j.envres.2021.112534 doi (DE-627)ELV007244614 (ELSEVIER)S0013-9351(21)01835-1 DE-627 ger DE-627 rda eng 333.7 610 VZ 44.13 bkl John, Esther M. verfasserin (orcid)0000-0003-3259-8003 aut Predictors of urinary polycyclic aromatic hydrocarbon metabolites in girls from the San Francisco Bay Area 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background: Polycyclic aromatic hydrocarbon (PAH) exposures from tobacco smoke, automobile exhaust, grilled or smoked meat and other sources are widespread and are a public health concern, as many are classified as probable carcinogens and suspected endocrine-disrupting chemicals. PAH exposures can be quantified using urinary biomarkers.Methods: Seven urinary metabolites of naphthalene, fluorene, phenanthrene, and pyrene were measured in two samples collected from girls aged 6–16 years from the San Francisco Bay Area. We used Spearman correlation coefficients (SCC) to assess correlations among metabolite concentrations (corrected for specific gravity) separately in first (n = 359) and last (N = 349) samples, and to assess consistency of measurements in samples collected up to 72 months apart. Using multivariable linear regression, we assessed variation in mean metabolites across categories of participant characteristics and potential outdoor, indoor, and dietary sources of PAH exposures.Results: The detection rate of PAH metabolites was high (4 metabolites in ≥98% of first samples; 5 metabolites in ≥95% of last samples). Correlations were moderate to strong between fluorene, phenanthrene and pyrene metabolites (SCC 0.43–0.82), but weaker between naphthalene and the other metabolites (SCC 0.18–0.36). SCC between metabolites in first and last samples ranged from 0.15 to 0.49. When classifying metabolite concentrations into tertiles based on single samples (first or last samples) vs. the average of the two samples, agreement was moderate to substantial (weighted kappa statistics 0.52–0.65). For specific metabolites, concentrations varied by age, race/ethnicity, and body mass index percentile, as well as by outdoor sources (season of sample collection, street traffic), indoor sources (heating with gas, cigarette smoke), and dietary sources (frequent use of grill, consumption of smoked meat or fish) of PAH exposures.Conclusions: Urinary PAH exposure was widespread in girls aged 6–16 years and associated with several sources of exposure. Tertile classification of a single urine sample provides reliable PAH exposure ranking. Biomarkers Children Epidemiology Polycyclic aromatic hydrocarbons (PAHs) Urinary metabolites Koo, Jocelyn verfasserin aut Ingles, Sue A. verfasserin aut Keegan, Theresa H. verfasserin (orcid)0000-0002-1961-4008 aut Nguyen, Jenny T. verfasserin aut Thomsen, Catherine verfasserin aut Terry, Mary Beth verfasserin aut Santella, Regina M. verfasserin (orcid)0000-0003-0823-6221 aut Nguyen, Khue verfasserin aut Yan, Beizhan verfasserin aut Enthalten in Environmental research San Diego, Calif. : Elsevier, 1967 205 Online-Ressource (DE-627)266876927 (DE-600)1467489-0 (DE-576)109967119 1096-0953 nnns volume:205 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 44.13 Medizinische Ökologie VZ AR 205
allfieldsGer	10.1016/j.envres.2021.112534 doi (DE-627)ELV007244614 (ELSEVIER)S0013-9351(21)01835-1 DE-627 ger DE-627 rda eng 333.7 610 VZ 44.13 bkl John, Esther M. verfasserin (orcid)0000-0003-3259-8003 aut Predictors of urinary polycyclic aromatic hydrocarbon metabolites in girls from the San Francisco Bay Area 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background: Polycyclic aromatic hydrocarbon (PAH) exposures from tobacco smoke, automobile exhaust, grilled or smoked meat and other sources are widespread and are a public health concern, as many are classified as probable carcinogens and suspected endocrine-disrupting chemicals. PAH exposures can be quantified using urinary biomarkers.Methods: Seven urinary metabolites of naphthalene, fluorene, phenanthrene, and pyrene were measured in two samples collected from girls aged 6–16 years from the San Francisco Bay Area. We used Spearman correlation coefficients (SCC) to assess correlations among metabolite concentrations (corrected for specific gravity) separately in first (n = 359) and last (N = 349) samples, and to assess consistency of measurements in samples collected up to 72 months apart. Using multivariable linear regression, we assessed variation in mean metabolites across categories of participant characteristics and potential outdoor, indoor, and dietary sources of PAH exposures.Results: The detection rate of PAH metabolites was high (4 metabolites in ≥98% of first samples; 5 metabolites in ≥95% of last samples). Correlations were moderate to strong between fluorene, phenanthrene and pyrene metabolites (SCC 0.43–0.82), but weaker between naphthalene and the other metabolites (SCC 0.18–0.36). SCC between metabolites in first and last samples ranged from 0.15 to 0.49. When classifying metabolite concentrations into tertiles based on single samples (first or last samples) vs. the average of the two samples, agreement was moderate to substantial (weighted kappa statistics 0.52–0.65). For specific metabolites, concentrations varied by age, race/ethnicity, and body mass index percentile, as well as by outdoor sources (season of sample collection, street traffic), indoor sources (heating with gas, cigarette smoke), and dietary sources (frequent use of grill, consumption of smoked meat or fish) of PAH exposures.Conclusions: Urinary PAH exposure was widespread in girls aged 6–16 years and associated with several sources of exposure. Tertile classification of a single urine sample provides reliable PAH exposure ranking. Biomarkers Children Epidemiology Polycyclic aromatic hydrocarbons (PAHs) Urinary metabolites Koo, Jocelyn verfasserin aut Ingles, Sue A. verfasserin aut Keegan, Theresa H. verfasserin (orcid)0000-0002-1961-4008 aut Nguyen, Jenny T. verfasserin aut Thomsen, Catherine verfasserin aut Terry, Mary Beth verfasserin aut Santella, Regina M. verfasserin (orcid)0000-0003-0823-6221 aut Nguyen, Khue verfasserin aut Yan, Beizhan verfasserin aut Enthalten in Environmental research San Diego, Calif. : Elsevier, 1967 205 Online-Ressource (DE-627)266876927 (DE-600)1467489-0 (DE-576)109967119 1096-0953 nnns volume:205 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 44.13 Medizinische Ökologie VZ AR 205
allfieldsSound	10.1016/j.envres.2021.112534 doi (DE-627)ELV007244614 (ELSEVIER)S0013-9351(21)01835-1 DE-627 ger DE-627 rda eng 333.7 610 VZ 44.13 bkl John, Esther M. verfasserin (orcid)0000-0003-3259-8003 aut Predictors of urinary polycyclic aromatic hydrocarbon metabolites in girls from the San Francisco Bay Area 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background: Polycyclic aromatic hydrocarbon (PAH) exposures from tobacco smoke, automobile exhaust, grilled or smoked meat and other sources are widespread and are a public health concern, as many are classified as probable carcinogens and suspected endocrine-disrupting chemicals. PAH exposures can be quantified using urinary biomarkers.Methods: Seven urinary metabolites of naphthalene, fluorene, phenanthrene, and pyrene were measured in two samples collected from girls aged 6–16 years from the San Francisco Bay Area. We used Spearman correlation coefficients (SCC) to assess correlations among metabolite concentrations (corrected for specific gravity) separately in first (n = 359) and last (N = 349) samples, and to assess consistency of measurements in samples collected up to 72 months apart. Using multivariable linear regression, we assessed variation in mean metabolites across categories of participant characteristics and potential outdoor, indoor, and dietary sources of PAH exposures.Results: The detection rate of PAH metabolites was high (4 metabolites in ≥98% of first samples; 5 metabolites in ≥95% of last samples). Correlations were moderate to strong between fluorene, phenanthrene and pyrene metabolites (SCC 0.43–0.82), but weaker between naphthalene and the other metabolites (SCC 0.18–0.36). SCC between metabolites in first and last samples ranged from 0.15 to 0.49. When classifying metabolite concentrations into tertiles based on single samples (first or last samples) vs. the average of the two samples, agreement was moderate to substantial (weighted kappa statistics 0.52–0.65). For specific metabolites, concentrations varied by age, race/ethnicity, and body mass index percentile, as well as by outdoor sources (season of sample collection, street traffic), indoor sources (heating with gas, cigarette smoke), and dietary sources (frequent use of grill, consumption of smoked meat or fish) of PAH exposures.Conclusions: Urinary PAH exposure was widespread in girls aged 6–16 years and associated with several sources of exposure. Tertile classification of a single urine sample provides reliable PAH exposure ranking. Biomarkers Children Epidemiology Polycyclic aromatic hydrocarbons (PAHs) Urinary metabolites Koo, Jocelyn verfasserin aut Ingles, Sue A. verfasserin aut Keegan, Theresa H. verfasserin (orcid)0000-0002-1961-4008 aut Nguyen, Jenny T. verfasserin aut Thomsen, Catherine verfasserin aut Terry, Mary Beth verfasserin aut Santella, Regina M. verfasserin (orcid)0000-0003-0823-6221 aut Nguyen, Khue verfasserin aut Yan, Beizhan verfasserin aut Enthalten in Environmental research San Diego, Calif. : Elsevier, 1967 205 Online-Ressource (DE-627)266876927 (DE-600)1467489-0 (DE-576)109967119 1096-0953 nnns volume:205 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 44.13 Medizinische Ökologie VZ AR 205
language	English
source	Enthalten in Environmental research 205 volume:205
sourceStr	Enthalten in Environmental research 205 volume:205
format_phy_str_mv	Article
bklname	Medizinische Ökologie
institution	findex.gbv.de
topic_facet	Biomarkers Children Epidemiology Polycyclic aromatic hydrocarbons (PAHs) Urinary metabolites
dewey-raw	333.7
isfreeaccess_bool	false
container_title	Environmental research
authorswithroles_txt_mv	John, Esther M. @@aut@@ Koo, Jocelyn @@aut@@ Ingles, Sue A. @@aut@@ Keegan, Theresa H. @@aut@@ Nguyen, Jenny T. @@aut@@ Thomsen, Catherine @@aut@@ Terry, Mary Beth @@aut@@ Santella, Regina M. @@aut@@ Nguyen, Khue @@aut@@ Yan, Beizhan @@aut@@
publishDateDaySort_date	2021-01-01T00:00:00Z
hierarchy_top_id	266876927
dewey-sort	3333.7
id	ELV007244614
language_de	englisch
fullrecord	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV007244614</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230927132516.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230506s2021 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.envres.2021.112534</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV007244614</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0013-9351(21)01835-1</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">333.7</subfield><subfield code="a">610</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">44.13</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">John, Esther M.</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0000-0003-3259-8003</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Predictors of urinary polycyclic aromatic hydrocarbon metabolites in girls from the San Francisco Bay Area</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2021</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Background: Polycyclic aromatic hydrocarbon (PAH) exposures from tobacco smoke, automobile exhaust, grilled or smoked meat and other sources are widespread and are a public health concern, as many are classified as probable carcinogens and suspected endocrine-disrupting chemicals. PAH exposures can be quantified using urinary biomarkers.Methods: Seven urinary metabolites of naphthalene, fluorene, phenanthrene, and pyrene were measured in two samples collected from girls aged 6–16 years from the San Francisco Bay Area. We used Spearman correlation coefficients (SCC) to assess correlations among metabolite concentrations (corrected for specific gravity) separately in first (n = 359) and last (N = 349) samples, and to assess consistency of measurements in samples collected up to 72 months apart. Using multivariable linear regression, we assessed variation in mean metabolites across categories of participant characteristics and potential outdoor, indoor, and dietary sources of PAH exposures.Results: The detection rate of PAH metabolites was high (4 metabolites in ≥98% of first samples; 5 metabolites in ≥95% of last samples). Correlations were moderate to strong between fluorene, phenanthrene and pyrene metabolites (SCC 0.43–0.82), but weaker between naphthalene and the other metabolites (SCC 0.18–0.36). SCC between metabolites in first and last samples ranged from 0.15 to 0.49. When classifying metabolite concentrations into tertiles based on single samples (first or last samples) vs. the average of the two samples, agreement was moderate to substantial (weighted kappa statistics 0.52–0.65). For specific metabolites, concentrations varied by age, race/ethnicity, and body mass index percentile, as well as by outdoor sources (season of sample collection, street traffic), indoor sources (heating with gas, cigarette smoke), and dietary sources (frequent use of grill, consumption of smoked meat or fish) of PAH exposures.Conclusions: Urinary PAH exposure was widespread in girls aged 6–16 years and associated with several sources of exposure. 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author	John, Esther M.
spellingShingle	John, Esther M. ddc 333.7 bkl 44.13 misc Biomarkers misc Children misc Epidemiology misc Polycyclic aromatic hydrocarbons (PAHs) misc Urinary metabolites Predictors of urinary polycyclic aromatic hydrocarbon metabolites in girls from the San Francisco Bay Area
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topic_title	333.7 610 VZ 44.13 bkl Predictors of urinary polycyclic aromatic hydrocarbon metabolites in girls from the San Francisco Bay Area Biomarkers Children Epidemiology Polycyclic aromatic hydrocarbons (PAHs) Urinary metabolites
topic	ddc 333.7 bkl 44.13 misc Biomarkers misc Children misc Epidemiology misc Polycyclic aromatic hydrocarbons (PAHs) misc Urinary metabolites
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title	Predictors of urinary polycyclic aromatic hydrocarbon metabolites in girls from the San Francisco Bay Area
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title_full	Predictors of urinary polycyclic aromatic hydrocarbon metabolites in girls from the San Francisco Bay Area
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author_browse	John, Esther M. Koo, Jocelyn Ingles, Sue A. Keegan, Theresa H. Nguyen, Jenny T. Thomsen, Catherine Terry, Mary Beth Santella, Regina M. Nguyen, Khue Yan, Beizhan
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title_sort	predictors of urinary polycyclic aromatic hydrocarbon metabolites in girls from the san francisco bay area
title_auth	Predictors of urinary polycyclic aromatic hydrocarbon metabolites in girls from the San Francisco Bay Area
abstract	Background: Polycyclic aromatic hydrocarbon (PAH) exposures from tobacco smoke, automobile exhaust, grilled or smoked meat and other sources are widespread and are a public health concern, as many are classified as probable carcinogens and suspected endocrine-disrupting chemicals. PAH exposures can be quantified using urinary biomarkers.Methods: Seven urinary metabolites of naphthalene, fluorene, phenanthrene, and pyrene were measured in two samples collected from girls aged 6–16 years from the San Francisco Bay Area. We used Spearman correlation coefficients (SCC) to assess correlations among metabolite concentrations (corrected for specific gravity) separately in first (n = 359) and last (N = 349) samples, and to assess consistency of measurements in samples collected up to 72 months apart. Using multivariable linear regression, we assessed variation in mean metabolites across categories of participant characteristics and potential outdoor, indoor, and dietary sources of PAH exposures.Results: The detection rate of PAH metabolites was high (4 metabolites in ≥98% of first samples; 5 metabolites in ≥95% of last samples). Correlations were moderate to strong between fluorene, phenanthrene and pyrene metabolites (SCC 0.43–0.82), but weaker between naphthalene and the other metabolites (SCC 0.18–0.36). SCC between metabolites in first and last samples ranged from 0.15 to 0.49. When classifying metabolite concentrations into tertiles based on single samples (first or last samples) vs. the average of the two samples, agreement was moderate to substantial (weighted kappa statistics 0.52–0.65). For specific metabolites, concentrations varied by age, race/ethnicity, and body mass index percentile, as well as by outdoor sources (season of sample collection, street traffic), indoor sources (heating with gas, cigarette smoke), and dietary sources (frequent use of grill, consumption of smoked meat or fish) of PAH exposures.Conclusions: Urinary PAH exposure was widespread in girls aged 6–16 years and associated with several sources of exposure. Tertile classification of a single urine sample provides reliable PAH exposure ranking.
abstractGer	Background: Polycyclic aromatic hydrocarbon (PAH) exposures from tobacco smoke, automobile exhaust, grilled or smoked meat and other sources are widespread and are a public health concern, as many are classified as probable carcinogens and suspected endocrine-disrupting chemicals. PAH exposures can be quantified using urinary biomarkers.Methods: Seven urinary metabolites of naphthalene, fluorene, phenanthrene, and pyrene were measured in two samples collected from girls aged 6–16 years from the San Francisco Bay Area. We used Spearman correlation coefficients (SCC) to assess correlations among metabolite concentrations (corrected for specific gravity) separately in first (n = 359) and last (N = 349) samples, and to assess consistency of measurements in samples collected up to 72 months apart. Using multivariable linear regression, we assessed variation in mean metabolites across categories of participant characteristics and potential outdoor, indoor, and dietary sources of PAH exposures.Results: The detection rate of PAH metabolites was high (4 metabolites in ≥98% of first samples; 5 metabolites in ≥95% of last samples). Correlations were moderate to strong between fluorene, phenanthrene and pyrene metabolites (SCC 0.43–0.82), but weaker between naphthalene and the other metabolites (SCC 0.18–0.36). SCC between metabolites in first and last samples ranged from 0.15 to 0.49. When classifying metabolite concentrations into tertiles based on single samples (first or last samples) vs. the average of the two samples, agreement was moderate to substantial (weighted kappa statistics 0.52–0.65). For specific metabolites, concentrations varied by age, race/ethnicity, and body mass index percentile, as well as by outdoor sources (season of sample collection, street traffic), indoor sources (heating with gas, cigarette smoke), and dietary sources (frequent use of grill, consumption of smoked meat or fish) of PAH exposures.Conclusions: Urinary PAH exposure was widespread in girls aged 6–16 years and associated with several sources of exposure. Tertile classification of a single urine sample provides reliable PAH exposure ranking.
abstract_unstemmed	Background: Polycyclic aromatic hydrocarbon (PAH) exposures from tobacco smoke, automobile exhaust, grilled or smoked meat and other sources are widespread and are a public health concern, as many are classified as probable carcinogens and suspected endocrine-disrupting chemicals. PAH exposures can be quantified using urinary biomarkers.Methods: Seven urinary metabolites of naphthalene, fluorene, phenanthrene, and pyrene were measured in two samples collected from girls aged 6–16 years from the San Francisco Bay Area. We used Spearman correlation coefficients (SCC) to assess correlations among metabolite concentrations (corrected for specific gravity) separately in first (n = 359) and last (N = 349) samples, and to assess consistency of measurements in samples collected up to 72 months apart. Using multivariable linear regression, we assessed variation in mean metabolites across categories of participant characteristics and potential outdoor, indoor, and dietary sources of PAH exposures.Results: The detection rate of PAH metabolites was high (4 metabolites in ≥98% of first samples; 5 metabolites in ≥95% of last samples). Correlations were moderate to strong between fluorene, phenanthrene and pyrene metabolites (SCC 0.43–0.82), but weaker between naphthalene and the other metabolites (SCC 0.18–0.36). SCC between metabolites in first and last samples ranged from 0.15 to 0.49. When classifying metabolite concentrations into tertiles based on single samples (first or last samples) vs. the average of the two samples, agreement was moderate to substantial (weighted kappa statistics 0.52–0.65). For specific metabolites, concentrations varied by age, race/ethnicity, and body mass index percentile, as well as by outdoor sources (season of sample collection, street traffic), indoor sources (heating with gas, cigarette smoke), and dietary sources (frequent use of grill, consumption of smoked meat or fish) of PAH exposures.Conclusions: Urinary PAH exposure was widespread in girls aged 6–16 years and associated with several sources of exposure. Tertile classification of a single urine sample provides reliable PAH exposure ranking.
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title_short	Predictors of urinary polycyclic aromatic hydrocarbon metabolites in girls from the San Francisco Bay Area
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author2	Koo, Jocelyn Ingles, Sue A. Keegan, Theresa H. Nguyen, Jenny T. Thomsen, Catherine Terry, Mary Beth Santella, Regina M. Nguyen, Khue Yan, Beizhan
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PAH exposures can be quantified using urinary biomarkers.Methods: Seven urinary metabolites of naphthalene, fluorene, phenanthrene, and pyrene were measured in two samples collected from girls aged 6–16 years from the San Francisco Bay Area. We used Spearman correlation coefficients (SCC) to assess correlations among metabolite concentrations (corrected for specific gravity) separately in first (n = 359) and last (N = 349) samples, and to assess consistency of measurements in samples collected up to 72 months apart. Using multivariable linear regression, we assessed variation in mean metabolites across categories of participant characteristics and potential outdoor, indoor, and dietary sources of PAH exposures.Results: The detection rate of PAH metabolites was high (4 metabolites in ≥98% of first samples; 5 metabolites in ≥95% of last samples). Correlations were moderate to strong between fluorene, phenanthrene and pyrene metabolites (SCC 0.43–0.82), but weaker between naphthalene and the other metabolites (SCC 0.18–0.36). SCC between metabolites in first and last samples ranged from 0.15 to 0.49. When classifying metabolite concentrations into tertiles based on single samples (first or last samples) vs. the average of the two samples, agreement was moderate to substantial (weighted kappa statistics 0.52–0.65). For specific metabolites, concentrations varied by age, race/ethnicity, and body mass index percentile, as well as by outdoor sources (season of sample collection, street traffic), indoor sources (heating with gas, cigarette smoke), and dietary sources (frequent use of grill, consumption of smoked meat or fish) of PAH exposures.Conclusions: Urinary PAH exposure was widespread in girls aged 6–16 years and associated with several sources of exposure. Tertile classification of a single urine sample provides reliable PAH exposure ranking.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Biomarkers</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Children</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Epidemiology</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Polycyclic aromatic hydrocarbons (PAHs)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Urinary metabolites</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Koo, Jocelyn</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ingles, Sue A.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield 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Predictors of urinary polycyclic aromatic hydrocarbon metabolites in girls from the San Francisco Bay Area

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