Background: Understanding the role of home food environment on gestational weight gain (GWG) may provide a useful weight management strategy to help reduce excessive GWG.
Materials And Methods: Pregnant women recruited between 2011 and 2014 (N = 165; normal weight N = 65, overweight N = 62, obese N = 38) in Arkansas completed measures of high-fat food availability, low-fat food availability, and food storage practices at baseline (4-10 weeks) and 30 weeks gestation. GWG was calculated as the difference between weight at the first (4-10 weeks) and final (36 weeks) prenatal visit, and based on each participant's baseline body mass index (BMI) category, GWG was classified as being above or within the 2009 Institute of Medicine's GWG guidelines. Multivariable models were adjusted for mother's age, race, marital status, and household income.
Results: There were no significant relationships between gaining above the guidelines and the home food environment variables. At baseline, after adjusting for covariates, overweight and obese pregnant women stored significantly more foods visibly in their home compared to normal weight women (overweight: β: 0.30, standard error [SE]: 0.13, p = 0.01; obese: β: 0.28, SE: 0.14, p = 0.04). At 30 weeks, obese pregnant women had significantly fewer low-fat foods in the home (β: -0.17; SE: 0.08, p = 0.04), although after adjusting for covariates, this relationship became a nonsignificant trend (p = 0.08). There were no significant relationships between BMI category and number of high-fat foods in the home.
Conclusions: These findings are consistent with other studies in nonpregnant populations that demonstrate that home food environment may influence weight status of overweight and obese pregnant women, although we did not find a significant relationship between the home food environment and GWG.
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http://dx.doi.org/10.1089/jwh.2017.6552 | DOI Listing |
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APC Microbiome Ireland, School of Microbiology, University College Cork, College Road, T12 K8AF Cork, Ireland.
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Centre for the Research and Technology of Agro-Environmental and Biological Sciences, University of Trás-os-Montes e Alto Douro, 5000-801 Vila Real, Portugal.
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Orobix Life, 24121 Bergamo, Italy.
We present an artificial intelligence (AI)-enhanced monitoring framework designed to assist personnel in evaluating and maintaining animal welfare using a modular architecture. This framework integrates multiple deep learning models to automatically compute metrics relevant to assessing animal well-being. Using deep learning for AI-based vision adapted from industrial applications and human behavioral analysis, the framework includes modules for markerless animal identification and health status assessment (e.
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Department of Industrial Engineering, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, Salerno, Italy.
Antioxidants are contained in fruits and vegetables and are commonly obtained through food. However, it is frequently necessary to supplement the diet with substances that are often poorly soluble in water and sensitive to light and oxygen. For this reason, in this work, luteolin (LUT) and naringenin (NAR), two compounds with antioxidant activity and potential health benefits, were precipitated through the supercritical antisolvent technique using polyvinylpyrrolidone and β-cyclodextrin as the carriers.
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December 2024
Department of Engineering, Pegaso Telematic University, 80143 Naples, Italy.
Lactic acid (LA) is a versatile, optically active compound with applications across the food, cosmetics, pharmaceutical, and chemical industries, largely driven by its role in producing biodegradable polylactic acid (PLA). Due to its abundance, lignocellulosic biomass is a promising and sustainable resource for LA production, although media derived from these matrices are often rich in xylose and contain growth inhibitors. This study investigates LA production using a xylose-rich medium derived from DC stalks treated through steam explosion and enzymatic hydrolysis.
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