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Hampson HE, Costello E, Walker DI, Wang H, Baumert BO, Valvi D, Rock S, Jones DP, Goran MI, Gilliland FD, Conti DV, Alderete TL, Chen Z, Chatzi L, Goodrich JA. Associations of dietary intake and longitudinal measures of per- and polyfluoroalkyl substances (PFAS) in predominantly Hispanic young Adults: A multicohort study. ENVIRONMENT INTERNATIONAL 2024; 185:108454. [PMID: 38316574 PMCID: PMC11089812 DOI: 10.1016/j.envint.2024.108454] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 12/14/2023] [Accepted: 01/18/2024] [Indexed: 02/07/2024]
Abstract
BACKGROUND Per- and polyfluoroalkyl substances (PFAS) are pollutants linked to adverse health effects. Diet is an important source of PFAS exposure, yet it is unknown how diet impacts longitudinal PFAS levels. OBJECTIVE To determine if dietary intake and food sources were associated with changes in blood PFAS concentrations among Hispanic young adults at risk of metabolic diseases. METHODS Predominantly Hispanic young adults from the Children's Health Study who underwent two visits (CHS; n = 123) and young adults from NHANES 2013-2018 who underwent one visit (n = 604) were included. Dietary data at baseline was collected using two 24-hour dietary recalls to measure individual foods and where foods were prepared/consumed (home/restaurant/fast-food). PFAS were measured in blood at both visits in CHS and cross-sectionally in NHANES. In CHS, multiple linear regression assessed associations of baseline diet with longitudinal PFAS; in NHANES, linear regression was used. RESULTS In CHS, all PFAS except PFDA decreased across visits (all p < 0.05). In CHS, A 1-serving higher tea intake was associated with 24.8 %, 16.17 %, and 12.6 % higher PFHxS, PFHpS, and PFNA at follow-up, respectively (all p < 0.05). A 1-serving higher pork intake was associated with 13.4 % higher PFOA at follow-up (p < 0.05). Associations were similar in NHANES, including unsweetened tea, hot dogs, and processed meats. For food sources, in CHS each 200-gram increase in home-prepared food was associated with 0.90 % and 1.6 % lower PFOS at baseline and follow-up, respectively, and in NHANES was associated with 0.9 % lower PFDA (all p < 0.05). CONCLUSION Results suggest that beverage consumption habits and food preparation are associated with differences in PFAS levels in young adults. This highlights the importance of diet in determining PFAS exposure and the necessity of public monitoring of foods and beverages for PFAS contamination.
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Affiliation(s)
- Hailey E Hampson
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, the United States of America
| | - Elizabeth Costello
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, the United States of America
| | - Douglas I Walker
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, the United States of America
| | - Hongxu Wang
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, the United States of America
| | - Brittney O Baumert
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, the United States of America
| | - Damaskini Valvi
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, the United States of America
| | - Sarah Rock
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, the United States of America
| | - Dean P Jones
- Clinical Biomarkers Laboratory, Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Emory University, Atlanta, GA, the United States of America
| | - Michael I Goran
- Department of Pediatrics, Keck School of Medicine, USC and The Saban Research Institute, Children's Hospital Los Angeles, Los Angeles, CA 90027, the United States of America
| | - Frank D Gilliland
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, the United States of America
| | - David V Conti
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, the United States of America
| | - Tanya L Alderete
- Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO, the United States of America
| | - Zhanghua Chen
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, the United States of America
| | - Leda Chatzi
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, the United States of America
| | - Jesse A Goodrich
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, the United States of America.
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Shen C, Ding M, Wu X, Cai G, Cai Y, Gai S, Wang B, Liu D. Identifying the quality characteristics of pork floss structure based on deep learning framework. Curr Res Food Sci 2023; 7:100587. [PMID: 37727873 PMCID: PMC10506091 DOI: 10.1016/j.crfs.2023.100587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 09/04/2023] [Accepted: 09/05/2023] [Indexed: 09/21/2023] Open
Abstract
Pork floss is a traditional Chinese food with a long history. Nowadays, pork floss is known to consumers as a leisure food. It is made from pork through a unique process in which the muscle fibers become flaky or granular and tangled. In this study, a deep learning-based approach is proposed to detect the quality characteristics of pork floss structure. Describe that the experiments were conducted using widely recognized brands of pork floss available in the grocery market, omitting the use of abbreviations. A total of 8000 images of eight commercially available pork flosses were collected and processed using sharpening, image gray coloring, real-time shading correction, and binarization. After the machine learning model learned the features of the pork floss, the images were labeled using a manual mask. The coupling of residual enhancement mask and region-based convolutional neural network (CRE-MRCNN) based deep learning framework was used to segment the images. The results showed that CRE-MRCNN could be used to identify the knot features and pore features of different brands of pork floss to evaluate their quality. The combined results of the models based on the sensory tests and machine vision showed that the pork floss from TC was the best, followed by YJJ, DD and HQ. This also shows the potential of machine vision to help people recognize the quality characteristics of pork floss structure.
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Affiliation(s)
- Che Shen
- College of Food Science and Technology, Bohai University, Jinzhou 121013, China
- Key Laboratory for Agricultural Products Processing of Anhui Province, School of Food Science and Engineering, Hefei University of Technology, Hefei, 230009, China
| | - Meiqi Ding
- College of Food Science and Technology, Bohai University, Jinzhou 121013, China
| | - Xinnan Wu
- College of Food Science and Technology, Bohai University, Jinzhou 121013, China
| | - Guanhua Cai
- College of Food Science and Technology, Bohai University, Jinzhou 121013, China
| | - Yun Cai
- College of Food Science and Technology, Bohai University, Jinzhou 121013, China
| | - Shengmei Gai
- College of Food Science and Technology, Bohai University, Jinzhou 121013, China
| | - Bo Wang
- College of Food Science and Technology, Bohai University, Jinzhou 121013, China
- Key Laboratory of Meat Processing and Quality Control, MOE, Key Laboratory of Meat Processing, MARA, College of Food Science and Technology, Nanjing Agricultural University, Nanjing 210095, China
- Institute of Ocean Research, Bohai University, Jinzhou 121013, Liaoning, China
| | - Dengyong Liu
- College of Food Science and Technology, Bohai University, Jinzhou 121013, China
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An HJ, Kim Y, Seo YG. Relationship between Coffee, Tea, and Carbonated Beverages and Cardiovascular Risk Factors. Nutrients 2023; 15:934. [PMID: 36839290 PMCID: PMC9966641 DOI: 10.3390/nu15040934] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 02/01/2023] [Accepted: 02/11/2023] [Indexed: 02/17/2023] Open
Abstract
We aimed to analyze the relationship between coffee, tea, and carbonated beverages and cardiovascular risk factors. We used data from the fourth to eighth Korea National Health and Nutrition Examination Surveys (2007-2016, 2019-2020). We categorized the frequency of intake into three groups (<1 time/week, 1 time/week to <1 time/day, and ≥1 time/day). Subsequently, logistic regression analyses by sex were performed to assess cardiovascular risk factors (hypertension (HTN), diabetes mellitus (DM), dyslipidemia (DL), or metabolic syndrome (MetS)) according to the frequency of coffee, tea, and carbonated beverage intake. For HTN, coffee intake showed an inverse relationship and tea intake showed a direct relationship. For DM, coffee intake showed an inverse relationship, and tea and carbonated beverage intake showed a direct relationship. For DL, coffee intake showed an inverse relationship, whereas tea intake demonstrated a direct relationship. In addition, carbonated beverage intake showed a direct relationship with MetS. Coffee intake showed an inverse relationship with HTN, DM, and DL. However, tea intake showed a direct relationship with HTN, DM, and DL, whereas carbonated beverage intake showed a direct relationship with DM and MetS.
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Affiliation(s)
| | | | - Young-Gyun Seo
- Department of Family Medicine, Hallym University Sacred Heart Hospital, Anyang 14068, Gyeonggi-do, Republic of Korea
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Mei T, Wang J, Xiao X, Lv J, Li Q, Dai H, Liu X, Pi F. Identification and Evaluation of Microplastics from Tea Filter Bags Based on Raman Imaging. Foods 2022; 11:2871. [PMID: 36140997 PMCID: PMC9497986 DOI: 10.3390/foods11182871] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 09/08/2022] [Accepted: 09/13/2022] [Indexed: 11/25/2022] Open
Abstract
Microplastic (MP) contamination is a public issue for the environment and for human health. Plastic-based food filter bags, including polyethylene terephthalate, polypropylene, nylon 6 (NY6), and polyethylene, are widely used for soft drink sub-packaging, increasing the risk of MPs in foods and the environment. Three types of commercially available filter bags, including non-woven and woven bags, were collected, and MPs released after soaking were mapped using Raman imaging combined with chemometrics. Compared with peak area imaging at a single characteristic peak, Raman imaging combined with direct classical least squares calculation was more efficient and reliable for identifying MP features. Up to 94% of the bags released MPs after soaking, and there was no significant correlation with soaking conditions. Most MPs were tiny fragments and particles, and a few were fibrous MPs 620-840 μm in size. Woven NY6 filter bags had the lowest risk of releasing MPs. Source exploration revealed that most MPs originated from fragments and particles adsorbed on the surface of bags and strings. The results of this study are applicable to filter bag risk assessment and provide scientific guidance for regulating MPs in food.
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Affiliation(s)
- Tingna Mei
- College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China
| | - Jiahua Wang
- College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China
- Hubei Key Laboratory for Processing and Transformation of Agricultural Products, Wuhan Polytechnic University, Wuhan 430023, China
| | - Xiaofeng Xiao
- College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China
| | - Jingwen Lv
- College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China
| | - Qiaocong Li
- College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China
| | - Huang Dai
- College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China
- Hubei Key Laboratory for Processing and Transformation of Agricultural Products, Wuhan Polytechnic University, Wuhan 430023, China
| | - Xiaodan Liu
- College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China
- Hubei Key Laboratory for Processing and Transformation of Agricultural Products, Wuhan Polytechnic University, Wuhan 430023, China
| | - Fuwei Pi
- College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China
- School of Food Science and Technology, Jiangnan University, Wuxi 214122, China
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Dhekne PP, Patwardhan AW. CFD model for transient flow fields around teabag during tea infusion. FOOD AND BIOPRODUCTS PROCESSING 2021. [DOI: 10.1016/j.fbp.2021.09.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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Optimization of a natural low-calorie antioxidant tea prepared from purple corn (Zea mays L.) cobs and stevia (Stevia rebaudiana Bert.). Lebensm Wiss Technol 2021. [DOI: 10.1016/j.lwt.2021.111952] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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Xu JL, Lin X, Hugelier S, Herrero-Langreo A, Gowen AA. Spectral imaging for characterization and detection of plastic substances in branded teabags. JOURNAL OF HAZARDOUS MATERIALS 2021; 418:126328. [PMID: 34118538 DOI: 10.1016/j.jhazmat.2021.126328] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 06/01/2021] [Accepted: 06/02/2021] [Indexed: 06/12/2023]
Abstract
The addition of plastic substances in teabags is of increasing concern for conscious consumers due to the harmful effects on the environment and the potential threats to human health. This work introduces an innovative and cost-effective approach to detect and quantify plastic substances in teabags by applying near infrared hyperspectral imaging (951-2496 nm) coupled with multivariate analysis. Teabags from 6 popular brands were investigated and categorized into three classes based on spectral unmixing and target detection results: 1) the plastic teabag primarily made of nylon 6/6; 2) those made of a composite with various polypropylene and cellulose ratios; 3) biodegradable teabags free from any plastic traces. Results demonstrated the presence of numerous plastic particles in the beverage obtained after steeping nylon teabags, but the release of particles was further amplified after microwave treatment. Nevertheless, target detection results obtained from Fourier transform infrared imaging (4000-675 cm-1) dataset evidenced that a considerable proportion of particle residues detected were the contaminants obtained from tea granules that adsorbed on the teabag. This work highlights the significant importance of performing rigorous spectral analysis for chemical characterization, which is lacking in most published microplastic studies.
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Affiliation(s)
- Jun-Li Xu
- School of Biosystems and Food Engineering, University College of Dublin (UCD), Belfield, Dublin 4, Ireland.
| | - Xiaohui Lin
- School of Biosystems and Food Engineering, University College of Dublin (UCD), Belfield, Dublin 4, Ireland
| | - Siewert Hugelier
- Laboratory for Nanobiology, Department of Chemistry, KU Leuven, B-3001 Leuven, Belgium
| | - Ana Herrero-Langreo
- School of Biosystems and Food Engineering, University College of Dublin (UCD), Belfield, Dublin 4, Ireland
| | - Aoife A Gowen
- School of Biosystems and Food Engineering, University College of Dublin (UCD), Belfield, Dublin 4, Ireland
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