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      Pre‐ and postnatal exposure to secondhand tobacco smoke and body composition at 12 years: periods of susceptibility

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          Abstract

          Objective

          The study aimed to identify periods of heightened susceptibility to the effects of pre‐ and postnatal secondhand tobacco smoke (SHS) exposure on body composition at age 12 years.

          Methods

          The study used data from 217 children from the Health Outcomes and Measures of the Environment (HOME) Study, a prospective cohort in Cincinnati, Ohio. Using multiple informant models, the study estimated associations of maternal serum cotinine (16 and 26 weeks of pregnancy) and child serum cotinine concentrations (at age 12, 24, 36, and 48 months) with measures of body composition obtained with anthropometry and dual‐energy x‐ray absorptiometry at 12 years. We examined whether there were differences between these associations for pre‐ and postnatal exposure periods and potential effect measure modification by sex.

          Results

          Postnatal cotinine concentrations were associated with higher weight, BMI, body fat and lean mass, waist circumference, and visceral, android, and gynoid fat. Each 10‐fold increase in postnatal cotinine was associated with 76% increased risk of overweight or obesity (95% CI: 1.13‐2.75). Associations between prenatal concentrations and measures of body composition at 12 years were generally null.

          Conclusions

          Postnatal exposure to SHS may increase adolescent adiposity and lean mass. Future studies should determine whether early‐life exposures to SHS are associated with other cardiometabolic risk markers.

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          Most cited references43

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          The State of US Health, 1990-2016

          Several studies have measured health outcomes in the United States, but none have provided a comprehensive assessment of patterns of health by state.
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            Environmental Chemicals in Pregnant Women in the United States: NHANES 2003–2004

            Background Exposure to chemicals during fetal development can increase the risk of adverse health effects, and while biomonitoring studies suggest pregnant women are exposed to chemicals, little is known about the extent of multiple chemicals exposures among pregnant women in the United States. Objective We analyzed biomonitoring data from the National Health and Nutritional Examination Survey (NHANES) to characterize both individual and multiple chemical exposures in U.S. pregnant women. Methods We analyzed data for 163 chemical analytes in 12 chemical classes for subsamples of 268 pregnant women from NHANES 2003–2004, a nationally representative sample of the U.S. population. For each chemical analyte, we calculated descriptive statistics. We calculated the number of chemicals detected within the following chemical classes: polybrominated diphenyl ethers (PBDEs), perfluorinated compounds (PFCs), organochlorine pesticides, and phthalates and across multiple chemical classes. We compared chemical analyte concentrations for pregnant and nonpregnant women using least-squares geometric means, adjusting for demographic and physiological covariates. Results The percentage of pregnant women with detectable levels of an individual chemical ranged from 0 to 100%. Certain polychlorinated biphenyls, organochlorine pesticides, PFCs, phenols, PBDEs, phthalates, polycyclic aromatic hydrocarbons, and perchlorate were detected in 99–100% of pregnant women. The median number of detected chemicals by chemical class ranged from 4 of 12 PFCs to 9 of 13 phthalates. Across chemical classes, median number ranged from 8 of 17 chemical analytes to 50 of 71 chemical analytes. We found, generally, that levels in pregnant women were similar to or lower than levels in nonpregnant women; adjustment for covariates tended to increase levels in pregnant women compared with nonpregnant women. Conclusions Pregnant women in the U.S. are exposed to multiple chemicals. Further efforts are warranted to understand sources of exposure and implications for policy making.
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              Nicotine chemistry, metabolism, kinetics and biomarkers.

              Nicotine underlies tobacco addiction, influences tobacco use patterns, and is used as a pharmacological aid to smoking cessation. The absorption, distribution and disposition characteristics of nicotine from tobacco and medicinal products are reviewed. Nicotine is metabolized primarily by the liver enzymes CYP2A6, UDPglucuronosyltransferase (UGT), and flavin-containing monooxygenase (FMO). In addition to genetic factors, nicotine metabolism is influenced by diet and meals, age, sex, use of estrogen-containing hormone preparations, pregnancy and kidney disease, other medications, and smoking itself. Substantial racial/ethnic differences are observed in nicotine metabolism, which are likely influenced by both genetic and environmental factors. The most widely used biomarker of nicotine intake is cotinine, which may be measured in blood, urine, saliva, hair, or nails. The current optimal plasma cotinine cut-point to distinguish smokers from non-smokers in the general US population is 3 ng ml(-1). This cut-point is much lower than that established 20 years ago, reflecting less secondhand smoke exposure due to clear air policies and more light or occasional smoking.
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                Author and article information

                Contributors
                monica.perez.rios@usc.es
                Journal
                Obesity (Silver Spring)
                Obesity (Silver Spring)
                10.1002/(ISSN)1930-739X
                OBY
                Obesity (Silver Spring, Md.)
                John Wiley and Sons Inc. (Hoboken )
                1930-7381
                1930-739X
                27 July 2022
                August 2022
                : 30
                : 8 ( doiID: 10.1002/oby.v30.8 )
                : 1659-1669
                Affiliations
                [ 1 ] Department of Preventive Medicine and Public Health Universidade de Santiago de Compostela Santiago de Compostela Spain
                [ 2 ] CIBEResp Madrid Spain
                [ 3 ] Department of Pediatrics, Cincinnati Children's Hospital Medical Center University of Cincinnati College of Medicine Cincinnati Ohio USA
                [ 4 ] Faculty of Health Sciences Simon Fraser University Vancouver British Columbia Canada
                [ 5 ] Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine University of Pennsylvania Philadelphia Pennsylvania USA
                [ 6 ] Department of Environmental Health and Engineering Johns Hopkins University Bloomberg School of Public Health Baltimore Maryland USA
                [ 7 ] Department of Pediatrics, Division of Gastroenterology, Hepatology & Nutrition, Cincinnati Children's Hospital Medical Center University of Cincinnati College of Medicine Cincinnati Ohio USA
                [ 8 ] Department of Radiology, Cincinnati Children's Hospital Medical Center University of Cincinnati College of Medicine Cincinnati Ohio USA
                [ 9 ] Department of Epidemiology Brown University Providence Rhode Island USA
                Author notes
                [*] [* ] Correspondence

                Mónica Pérez‐Ríos, Department of Preventive Medicine and Public Health, University of Santiago de Compostela, Santiago de Compostela, Spain.

                Email: monica.perez.rios@ 123456usc.es

                Author information
                https://orcid.org/0000-0003-2008-5913
                https://orcid.org/0000-0002-5239-3235
                Article
                OBY23480
                10.1002/oby.23480
                9335905
                35894081
                9b79987f-d168-493c-a711-36bbf435e300
                © 2022 The Authors. Obesity published by Wiley Periodicals LLC on behalf of The Obesity Society (TOS).

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                : 28 March 2022
                : 21 January 2022
                : 01 May 2022
                Page count
                Figures: 2, Tables: 5, Pages: 11, Words: 8142
                Funding
                Funded by: National Institute of Environmental Health Sciences , doi 10.13039/100000066;
                Award ID: P01 ES011261
                Award ID: R01 ES014575
                Award ID: R01 ES015517
                Categories
                Original Article
                ORIGINAL ARTICLES
                Pediatric Obesity
                Custom metadata
                2.0
                August 2022
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.2.0 mode:remove_FC converted:07.10.2022

                Medicine
                Medicine

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