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Journal articles on the topic 'Dietary analysis'

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Published: 4 June 2021

Last updated: 20 February 2023

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1

McCleary, Barry V. "Dietary fibre analysis." Proceedings of the Nutrition Society 62, no. 1 (February 2003): 3–9. http://dx.doi.org/10.1079/pns2002204.

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The 'gold standard' method for the measurement of total dietary fibre is that of the Association of Official Analytical Chemists (2000; method 985.29). This procedure has been modified to allow measurement of soluble and insoluble dietary fibre, and buffers employed have been improved. However, the recognition of the fact that non-digestible oligosaccharides and resistant starch also behave physiologically as dietaryfibre has necessitated a re-examination of the definition of dietary fibre, and in turn, a re-evaluation of the dietary fibre methods of the Association of Official Analytical Chemists. With this realisation, the American Association of Cereal Chemists appointed a scientific review committee and charged it with the task of reviewing and, if necessary, updating the definition of dietary fibre. It organised various workshops and acceptedcomments from interested parties worldwide through an interactive website. More recently, the (US) Food and Nutrition Board of the Institute of Health, National Academy of Sciences, under the oversight of the Standing Committee on the Scientific Evaluation of Dietary Reference Intakes, assembled a panel to develop a proposed definition(s) of dietary fibre. Various elements of these definitions were in agreement, but not all. What was clear from both reviews is that there is an immediate need to re-evaluate the methods that are used for dietary fibre measurement and to make appropriate changes where required, and to find new methods to fill gaps. In this presentation, the 'state of the art' in measurement of total dietary fibre and dietary fibre components will be described and discussed, together with suggestions for future research.

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2

Kosseva, M. R., and John F. Kennedy. "Dietary fibre analysis." Carbohydrate Polymers 34, no. 4 (December 1997): 419. http://dx.doi.org/10.1016/s0144-8617(97)87332-8.

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3

Knudsen, Knud Erik Bach. "Dietary fibre analysis." TrAC Trends in Analytical Chemistry 16, no. 5 (May 1997): XI—XII. http://dx.doi.org/10.1016/s0165-9936(97)89789-0.

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4

Ferreira, Karen Carvalho, Juliana Aparecida Correia Bento, Lázaro Sátiro De Jesus, and Priscila Zaczuk Bassinelo. "DIETARY FIBERS: ANALYSIS METHODS." Científic@ - Multidisciplinary Journal 5, no. 3 (November 13, 2018): 174–79. http://dx.doi.org/10.29247/2358-260x.2018v5i3.p174-179.

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Dietary fiber (DF) intake is associated with a number of benefits and these effects depend not only on intake as well as its composition. The DF includes polysaccharides such as cellulose, hemicellulose, pectins, gums, oligosaccharides and lignin, and can be divided into soluble and insoluble. The concept of DF was expanded to include resistant starch, inulin and fructo-oligosaccharides. The determination of DF costly and time depends on methods that have been modified for this new concept. The AOAC Official methods of determining all components present in a DF, without specific methods for each component. Studies show innovative techniques to ensure a shorter analysis time, less waste generation by the use of reagents and more convenience in the analysis.

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Perloff, Betty P. "Analysis of dietary data." American Journal of Clinical Nutrition 50, no. 5 (November 1, 1989): 1128–32. http://dx.doi.org/10.1093/ajcn/50.5.1128.

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6

Solans, M., G. Coenders, R. Marcos-Gragera, A. Castelló, E. Gràcia-Lavedan, Y. Benavente, V. Moreno, et al. "Compositional analysis of dietary patterns." Statistical Methods in Medical Research 28, no. 9 (July 26, 2018): 2834–47. http://dx.doi.org/10.1177/0962280218790110.

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Instead of looking at individual nutrients or foods, dietary pattern analysis has emerged as a promising approach to examine the relationship between diet and health outcomes. Despite dietary patterns being compositional (i.e. usually a higher intake of some foods implies that less of other foods are being consumed), compositional data analysis has not yet been applied in this setting. We describe three compositional data analysis approaches (compositional principal component analysis, balances and principal balances) that enable the extraction of dietary patterns by using control subjects from the Spanish multicase-control (MCC-Spain) study. In particular, principal balances overcome the limitations of purely data-driven or investigator-driven methods and present dietary patterns as trade-offs between eating more of some foods and less of others.

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Asp, Nils-Georg, Ivan Furda, Jonathan W. DeVries, Thomas F. Schweizer, and Leon Prosky. "Dietary fiber definition and analysis." American Journal of Clinical Nutrition 48, no. 3 (September 1, 1988): 688–90. http://dx.doi.org/10.1093/ajcn/48.3.688-a.

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8

&NA;. "Free Communication/Slide - Dietary Analysis." Medicine & Science in Sports & Exercise 40, Supplement (May 2008): 40. http://dx.doi.org/10.1249/01.mss.0000320875.66895.8a.

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9

Lambert, Joseph B., Sharon Vlasak, Simpson, Carole B. Szpunar, and Jane E. Buikstra. "Bone diagenesis and dietary analysis." Journal of Human Evolution 14, no. 5 (July 1985): 477–82. http://dx.doi.org/10.1016/s0047-2484(85)80026-9.

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10

Imamura, F., and P. F. Jacques. "Invited Commentary: Dietary Pattern Analysis." American Journal of Epidemiology 173, no. 10 (April 7, 2011): 1105–8. http://dx.doi.org/10.1093/aje/kwr063.

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11

Asp, Nils-Georg. "Definition and analysis of dietary fibre." Scandinavian Journal of Gastroenterology 22, sup129 (January 1987): 16–20. http://dx.doi.org/10.3109/00365528709095845.

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12

Graham, John H., and Robert C. Vrijenhoek. "Detrended Correspondence Analysis of Dietary Data." Transactions of the American Fisheries Society 117, no. 1 (January 1988): 29–36. http://dx.doi.org/10.1577/1548-8659(1988)117<0029:dcaodd>2.3.co;2.

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13

Carrington, Clark D., P. Michael Bolger, and Robert J. Scheuplein. "Risk analysis of dietary lead exposure." Food Additives & Contaminants 13, no. 1 (January 1996): 61–76. http://dx.doi.org/10.1080/02652039609374381.

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14

Harrison, Caleb D., Robert Pawlak, Brycen J. Ratcliffe, Francisco Morales, Colin Carriker, and Alvaro N. Gurovich. "Dietary Nitrate and Pulse Wave Analysis." Medicine & Science in Sports & Exercise 49, no. 5S (May 2017): 818. http://dx.doi.org/10.1249/01.mss.0000519192.53361.55.

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15

Theander, Olof, Per Åman, Eric Westerlund, and Hadden Graham. "Enzymatic/Chemical Analysis of Dietary Fiber." Journal of AOAC INTERNATIONAL 77, no. 3 (May 1, 1994): 703–9. http://dx.doi.org/10.1093/jaoac/77.3.703.

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Abstract The Uppsala methodology for rapid analysis and characterization of total dietary fiber, defined as the sum of dietary fiber polysaccharides (DFP) and Klason lignin, was studied. A sugar- and starch-free residue was prepared by treatment with a thermo-stable amylase and amyloglucosidase. Neutral DFP residues were quantified by gas chromatography as alditol acetates after acid hydrolysis of this residue, and the acidinsoluble fraction, Klason lignin, was determined gravimetricaliy. Uronic acid residues were quantified by decarboxylation of the original sample. The efficacy of the Uppsala methodology was tested with foods varying in fiber content and composition, including heat-treated samples. The present method allowed the analysis of up to 40 samples per week. It had good repeatability and coefficients of variation of 3-5% for the main fiber components. Fiber contents determined with the method were higher than those determined with a similar method that excludes Klason lignin and starch resistant to amylases but soluble in dimethyl sulfoxide and lower than those determined with an enzymatic/gravimetric method. Important aspects of fiber analysis, like enzyme purity and the recovery of soluble fiber on ethanol precipitation, also were investigated.

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16

RATNAYAKE, W. M. N. "Analysis of Dietary Trans Fatty Acids." Journal of Oleo Science 50, no. 5 (2001): 339–52. http://dx.doi.org/10.5650/jos.50.339.

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17

Seaman, Claire. "More computer software for dietary analysis." Journal of Human Nutrition and Dietetics 6, no. 2 (April 1993): 171–72. http://dx.doi.org/10.1111/j.1365-277x.1993.tb00360.x.

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18

Komarek, A. R. "Dietary Fiber Analysis: Challenges of Automation." Cereal Foods World 57, no. 2 (March 2012): 50–54. http://dx.doi.org/10.1094/cfw-57-2-0050.

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19

Butler, Richard Charles, and Javid Patel. "A direction in dietary fibre analysis." Nutrition & Food Science 30, no. 5 (October 2000): 221–26. http://dx.doi.org/10.1108/00346650010340918.

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20

Theander, Olof, and Eric A. Westerlund. "Studies on dietary fiber. 3. Improved procedures for analysis of dietary fiber." Journal of Agricultural and Food Chemistry 34, no. 2 (March 1986): 330–36. http://dx.doi.org/10.1021/jf00068a045.

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21

Hua, Katheline. "Investigating the appropriate mode of expressing lysine requirement of fish through non-linear mixed model analysis and multilevel analysis." British Journal of Nutrition 109, no. 6 (July 24, 2012): 1013–21. http://dx.doi.org/10.1017/s0007114512002863.

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Accurate estimates of lysine requirement are essential to fish feed formulation. However, controversy exists regarding the most appropriate mode to express lysine requirement. In the fish nutrition literature, essential amino acid (AA) requirement has been expressed as a percentage of diet, a percentage of dietary crude protein or a ratio to dietary digestible energy (DE). The controversy lies in the different assumptions regarding the effects of dietary protein and DE on lysine requirement. Non-linear mixed model analysis and multilevel analysis were carried out to investigate whether dietary protein or DE affected lysine requirement of fish. The non-linear mixed model analysis suggests that expressing lysine requirement as a percentage of dietary protein provides a better goodness of fit to the modelling dataset than expressing requirement as a fixed concentration of diet, which in turn is generally better than expressing requirement as a ratio to DE. Results from the multilevel analysis confirm that dietary protein content has a significant effect on lysine requirement, while DE does not. The findings of the present study could contribute to a better understanding of the underlying dietary factors that affect AA requirements of fish. The results of the present study could also be useful for developing nutritional guidelines and feed formulations for fish.

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22

Devi, A. R. Sudha, and M. K. Smija M.K. Smija. "Analysis of dietary value of the soft tissue of the freshwater crab Travancoriana schirnerae." Indian Journal of Applied Research 3, no. 7 (October 1, 2011): 45–49. http://dx.doi.org/10.15373/2249555x/july2013/13.

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23

Spears, L. R., and R. H. Crompton. "Finite Elements Stress Analysis as a possible tool for reconstruction of hominid dietary mechanics." Zeitschrift für Morphologie und Anthropologie 80, no. 1 (November 29, 1994): 3–17. http://dx.doi.org/10.1127/zma/80/1994/3.

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24

Liu, Aiwen, Siti Ratna Komala, and Lin Feng. "Analysis Of Dietary Structure Of Chinese Volleyball Athletes By Dietary Balance Index Method." Medicine & Science in Sports & Exercise 54, no. 9S (September 2022): 486. http://dx.doi.org/10.1249/01.mss.0000881188.61198.25.

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25

Liew, Hui-Peng. "Dietary habits and physical activity: Results from cluster analysis and market basket analysis." Nutrition and Health 24, no. 2 (May 10, 2018): 83–92. http://dx.doi.org/10.1177/0260106018770942.

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Background: The prevalence of obesity remains a major public health concern and there has been a significant increase in childhood obesity in the USA. Aim: This study seeks to uncover the major patterns of dietary habits in relation to physical activity, together with students’ opinions about the quality of food in the school’s cafeteria and vending machines. Methods: The empirical work of this study is based on the 2011 Healthy School Program (HSP) Evaluation. HSP assesses the demographic characteristics as well as the dietary habits and exercise patterns of a representative sample of elementary, middle, and high school students in the USA. Results: Findings suggest that students assigned to different clusters have different eating habits, exercise patterns, weight status, weight management, and opinions about the quality of food in the school’s cafeteria and vending machines. There is great variation in dietary profiles and lifestyle behaviors among students who identified themselves as either overweight or unsure about their weight status. Conclusions: Findings from this study may inform future interventions regarding how to promote student’s healthy food choices when they are still in school. Health promotion initiatives should specifically target students with persistently unhealthier dietary profiles.

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26

Eduardo Corrente, José, Giovana Fumes-Ghantous, and Rafaela Vitoria Trombacco Barbosa. "Obtaining Dietary Patterns Through Factor Analysis Techniques." Acta Scientifci Nutritional Health 3, no. 11 (October 28, 2019): 215–19. http://dx.doi.org/10.31080/asnh.2019.03.0515.

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27

Frank, Gail C., and Suzanne Pelican. "Guidelines for selecting a dietary analysis system." Journal of the American Dietetic Association 86, no. 1 (January 1986): 72–75. http://dx.doi.org/10.1016/s0002-8223(21)03887-6.

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28

McLaughlin, Kelly C., Lauren N. Chavis, Rachel Dickinson, Emily Reeve, Christian K. Roberts, and Deborah L. Feairheller. "Analysis of Dietary Intake in Volunteer Firefighters." Medicine & Science in Sports & Exercise 49, no. 5S (May 2017): 110. http://dx.doi.org/10.1249/01.mss.0000517127.98423.84.

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29

Nikolaev, N. A. Nikolaev (), Yu P. Skirdenko (. Skirdenko, ). ), M. A. Livzan () Livzan, M. V. Kolbina () Kolbina, M. B. Kostenko () Kostenko, and M. A. Makeykina () Makeykina. "CLINICALLY IMPORTANT DIETARY PREFERENCES: EVALUATION, ANALYSIS, INTERPRETATION." Pharmateca 9_2018 (October 15, 2018): 85–88. http://dx.doi.org/10.18565/pharmateca.2018.9.85-88.

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30

Southgate, D. A. T. "The Definiton and Analysis of Dietary Fibre." Nutrition Reviews 35, no. 3 (April 27, 2009): 31–37. http://dx.doi.org/10.1111/j.1753-4887.1977.tb06534.x.

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31

Bach Knudsen, K. E. "The nutritional significance of “dietary fibre” analysis." Animal Feed Science and Technology 90, no. 1-2 (March 2001): 3–20. http://dx.doi.org/10.1016/s0377-8401(01)00193-6.

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32

Gaull, G. E., T. Giombetti, and R. W. Woo. "Pediatric dietary lipid guidelines: a policy analysis." Journal of the American College of Nutrition 14, no. 5 (October 1995): 411–18. http://dx.doi.org/10.1080/07315724.1995.10718531.

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33

ELISABET WIRFÄLT, A. K., and ROBERT W. JEFFERY. "Using Cluster Analysis to Examine Dietary Patterns." Journal of the American Dietetic Association 97, no. 3 (March 1997): 272–79. http://dx.doi.org/10.1016/s0002-8223(97)00071-0.

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34

Güttler, Fleming, and Per Guldberg. "Mutation analysis anticipates dietary requirements in phenylketonuria." European Journal of Pediatrics 159, S2 (September 4, 2000): S150—S153. http://dx.doi.org/10.1007/pl00014381.

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35

Mañas, E., L. Bravo, and F. Saura-Calixto. "Sources of error in dietary fibre analysis." Food Chemistry 50, no. 4 (January 1994): 331–42. http://dx.doi.org/10.1016/0308-8146(94)90201-1.

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36

Gerard, K., P. Guy, R. Paluch, and K. Kong. "Nutritional Analysis of Dietary Recalls on Infants." Journal of the Academy of Nutrition and Dietetics 118, no. 9 (September 2018): A42. http://dx.doi.org/10.1016/j.jand.2018.06.161.

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37

Green, Gary A., Don H. Catlin, and Borislav Starcevic. "Analysis of Over-the-Counter Dietary Supplements." Clinical Journal of Sport Medicine 11, no. 4 (October 2001): 254–59. http://dx.doi.org/10.1097/00042752-200110000-00008.

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38

Clarke, M. "Computerized dietary analysis: a truly interactive approach." Journal of Human Nutrition and Dietetics 2, no. 4 (August 1989): 287–93. http://dx.doi.org/10.1111/j.1365-277x.1989.tb00031.x.

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39

Bauer Petrovska, Biljana, S. Kulevanova, and V. Stefov. "Infrared analysis of Macedonian mushroom dietary fibre." Nahrung/Food 46, no. 4 (July 1, 2002): 238. http://dx.doi.org/10.1002/1521-3803(20020701)46:4<238::aid-food238>3.0.co;2-a.

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40

Rimmer, Catherine A., Katherine E. Sharpless, Stephen A. Wise, Joseph M. Betz, and Paul M. Coates. "Standard reference materials for dietary supplement analysis." Analytical and Bioanalytical Chemistry 405, no. 13 (April 11, 2013): 4337–44. http://dx.doi.org/10.1007/s00216-013-6942-x.

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41

Joo, Jaehyun, Sinead A. Williamson, Ana I. Vazquez, Jose R. Fernandez, and Molly S. Bray. "Advanced Dietary Patterns Analysis Using Sparse Latent Factor Models in Young Adults." Journal of Nutrition 148, no. 12 (November 9, 2018): 1984–92. http://dx.doi.org/10.1093/jn/nxy188.

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ABSTRACT Background Principal components analysis (PCA) has been the most widely used method for deriving dietary patterns to date. However, PCA requires arbitrary ad hoc decisions for selecting food variables in interpreting dietary patterns and does not easily accommodate covariates. Sparse latent factor models can be utilized to address these issues. Objective The objective of this study was to compare Bayesian sparse latent factor models with PCA for identifying dietary patterns among young adults. Methods Habitual food intake was estimated in 2730 sedentary young adults from the Training Interventions and Genetics of Exercise Response (TIGER) Study [aged 18–35 y; body mass index (BMI; in kg/m2): 26.5 ± 6.1] who exercised <30 min/wk during the previous 30 d without restricting caloric intake before study enrollment. A food-frequency questionnaire was used to generate the frequency intakes of 102 food items. Sparse latent factor modeling was applied to the standardized food intakes to derive dietary patterns, incorporating additional covariates (sex, race/ethnicity, and BMI). The identified dietary patterns via sparse latent factor modeling were compared with the PCA derived dietary patterns. Results Seven dietary patterns were identified in both PCA and sparse latent factor analysis. In contrast to PCA, the sparse latent factor analysis allowed the covariate information to be jointly accounted for in the estimation of dietary patterns in the model and offered probabilistic criteria to determine the foods relevant to each dietary pattern. The derived patterns from both methods generally described common dietary behaviors. Dietary patterns 1–4 had similar food subsets using both statistical approaches, but PCA had smaller sets of foods with more cross-loading elements between the 2 factors. Overall, the sparse latent factor analysis produced more interpretable dietary patterns, with fewer of the food items excluded from all patterns. Conclusion Sparse latent factor models can be useful in future studies of dietary patterns by reducing the intrinsic arbitrariness involving the choice of food variables in interpreting dietary patterns and incorporating covariates in the assessment of dietary patterns.

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Batis, Carolina, Daniela Sotres-Alvarez, Penny Gordon-Larsen, Michelle A. Mendez, Linda Adair, and Barry Popkin. "Longitudinal analysis of dietary patterns in Chinese adults from 1991 to 2009." British Journal of Nutrition 111, no. 8 (December 13, 2013): 1441–51. http://dx.doi.org/10.1017/s0007114513003917.

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In the present study, we aimed to identify the changes or stability in the structure of dietary patterns and tracking, trends and factors related to the adherence to these dietary patterns in China from 1991 to 2009. We analysed dietary data collected during seven waves of the China Health and Nutrition Survey and included 9253 adults with complete dietary data for three or more waves. Dietary intake assessment was carried out over a 3 d period with 24 h recalls and a household food inventory. Using factor analysis in each wave, we found that the structure of the two dietary patterns identified remained stable over the studied period. The traditional southern dietary pattern was characterised by high intakes of rice, fresh leafy vegetables, low-fat red meat, pork, organ meats, poultry and fish/seafood and low intakes of wheat flour and maize/coarse grains and the modern high-wheat dietary pattern was characterised by high intakes of wheat buns/breads, cakes/cookies/pastries, deep-fried wheat, nuts/seeds, starchy root/tuber products, fruits, eggs/egg products, soya milk, animal-based milk and instant noodles/frozen dumplings. Temporal tracking (maintenance of a relative position over time) was higher for the traditional southern dietary pattern, whereas adherence to the modern high-wheat dietary pattern had an upward trend over time. Higher income, education and urbanicity levels were positively associated with both the dietary patterns, but the association became weaker in the later years. These results suggest that even in the context of rapid economic changes in China, the way people chose to combine their foods remained relatively stable. However, the increasing popularity of the modern high-wheat dietary pattern, a pattern associated with several energy-dense foods, is a cause of concern.

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43

Fuster, Melissa. "Comparative analysis of dietary guidelines in the Spanish-Speaking Caribbean." Public Health Nutrition 19, no. 4 (July 10, 2015): 607–15. http://dx.doi.org/10.1017/s1368980015002153.

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AbstractObjectiveDietary guidelines are important education and policy tools to address local nutrition concerns. The current paper presents a comparative analysis of nutrition messages from three Spanish-speaking Caribbean countries (Cuba, Puerto Rico and Dominican Republic) to explore how these dietary guidelines address common public health nutrition concerns, contextualized in different changing food environments and food culture similarities.DesignQualitative, comparative analysis of current dietary guideline documents and key recommendations.ResultsKey recommendations were categorized into sixteen themes (two diet-based, ten food-based and four ‘other’). Only the Cuban dietary guidelines included diet-based key recommendations. Of the ten food-based key recommendations, only four themes overlapped across the three dietary guidelines (the encouragement of fruits and vegetables, addressing protein sources and fat). Other overlaps were found between dietary guideline pairs, except between Cuba and Puerto Rico. Further analysis revealed differences in levels of specificity and acknowledgement of local dietary patterns and issues, as well as the need to revise the guidelines to account for current scientific advances.ConclusionsThe present study underscored the importance of context in the framing of dietary advice and the influence of national socio-economic and political situations on nutrition policy and education efforts. The results contribute to inform efforts to improve nutrition communication in the region and among migrant communities.

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Václavíková, E., and F. Kvasnička. "Isotachophoretic determination of glucosamine and chondroitin sulphate in dietary supplements." Czech Journal of Food Sciences 31, No. 1 (January 10, 2013): 55–65. http://dx.doi.org/10.17221/107/2012-cjfs.

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Glucosamine and chondroitin sulfate, components of normal cartilage, are used as ingredients in dietary supplements intended to treat osteoarthritis and/or to support joint health. Of concern is the documented lack of quality in many of the marketed products. We present here a capillary isotachophoretic method for the determination of glucosamine and chondroitin sulfate in dietary supplements. Cationic analysis of glucosamine was performed with a leading electrolyte consisting of 10mM NH<sub>4</sub>OH + 20mM acetic acid. As the leading electrolyte for anionic analysis of chondroitin sulphate, a mixture of 5mM HCl + 10mM glycylglycine + 0.05% of 2-hydroxyethylcellulose was used. The solution of 10mM citric acid served as the terminating electrolyte for both glucosamine and chondroitin sulfate analyses. The analytes were detected by conductivity and UV detectors. The characteristics of the method,, i.e., linearity, accuracy, repeatability, and quantitation limit, were evaluated. On a set of 35 samples of marketed dietary supplements did we prove that the capillary isotachophoresis is a suitable method for the routine analysis of glucosamine and chondroitin sulfate.  

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Parvizian, Michael K., Manreet Dhaliwal, Jeremy Li, Imran Satia, and Om P. Kurmi. "Relationship between dietary patterns and COPD: a systematic review and meta-analysis." ERJ Open Research 6, no. 2 (April 2020): 00168–2019. http://dx.doi.org/10.1183/23120541.00168-2019.

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BackgroundFindings from previous studies reporting on the associations between chronic obstructive pulmonary disease (COPD) and various dietary patterns have been inconsistent. This review aims to summarise the evidence on the strength of the association between dietary patterns and the prevalence and incidence of COPD.MethodsWe conducted a comprehensive search of seven databases between 1 January 1980 and 30 November 2019. Two reviewers independently reviewed each manuscript through the screening, selection, data extraction and quality assessment stages. Data from eight observational studies that met the inclusion criteria were extracted and random-effects meta-analysis was subsequently conducted.ResultsEight observational studies (all eight reporting on healthy dietary patterns and three on unhealthy dietary patterns) met the inclusion criteria and data were extracted to include in the meta-analysis. Consumption of a healthy dietary pattern was associated with a lower risk of COPD (pooled OR 0.88, 95% CI 0.82–0.94). Consumption of unhealthy dietary patterns was associated with a higher risk of COPD (OR 1.22, 95% CI 0.84–1.76); however, the results were not statistically significant and had high heterogeneity (I2=91%).ConclusionOur results suggests that healthy dietary patterns are associated with a lower prevalence of COPD, while unhealthy dietary patterns are not. More studies, particularly adequately powered longitudinal studies, are needed to further elucidate the effects of healthy and unhealthy dietary patterns on risk of COPD.

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46

Maslov, O. Yu, S. V. Kolisnyk, M. A. Komisarenko, S. M. Poluian, M. Yu Holik, and T. O. Tomarovska. "Analysis of pharmaceutical market of dietary supplements with green tea leaves extract." Current issues in pharmacy and medicine: science and practice 15, no. 1 (February 15, 2022): 40–45. http://dx.doi.org/10.14739/2409-2932.2022.1.252651.

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The aim of work is to study the assortment of dietary supplements with green tea leaves extract on the modern pharmaceutical market to further search for ways to improve and optimize pharmaceutical supply. Materials and methods. The assortment of dietary supplements with green tea leaves extract was studied basing on the search of dietary supplements in pharmacies of Ukraine in the internet resources. For study of assortment of dietary supplements, the following methods were used: marketing, statistical, logic and graphic. Results. The assortment of dietary supplements with green tea leaves extract has been analyzed. The results showed that the leaders in the number of manufacturers in the analyzed group of dietary supplements are the United States, Ukraine, and Poland, their part is 61 %, 16 % and 8 %, respectively. In terms of assortment, the United States ranks first – 66 %. Dietary supplements are presented in 6 dosage forms, most of them are capsules (60 %). It was determined that monopreparations predominate in the pharmaceutical market and account for 77 %. The price segmentation of the market of dietary supplements with green tea leaves extract has been provided, the results showed that most of these are dietary supplements in the price range of 200–500 UAH. The study of the company structure made it possible to identify leaders among foreign companies; the top three companies included Now Foods (27 %), Swanson (20 %), Puritan’s Pride (14 %). Conclusions. There are 42 dietary supplements with green tea leaves extract at the beginning of 2022 in Ukraine. On the temporary pharmaceutical market of Ukraine 84 % of dietary supplements with green tea extract are presented by foreign manufacturers, mainly by monopreparations, in the form of capsules and in the price range from 200 to 500 UAH.

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Ho, Chiou Yi, Zuriati Ibrahim, Zalina Abu Zaid, Zulfitri Azuan Mat Daud, Nor Baizura Mohd Yusop, Mohd Norazam Mohd Abas, and Jamil Omar. "Postoperative Dietary Intake Achievement: A Secondary Analysis of a Randomized Controlled Trial." Nutrients 14, no. 1 (January 5, 2022): 222. http://dx.doi.org/10.3390/nu14010222.

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Sufficient postoperative dietary intake is crucial for ensuring a better surgical outcome. This study aimed to investigate the postoperative dietary intake achievement and predictors of postoperative dietary intake among gynecologic cancer patients. A total of 118 participants were included in this secondary analysis. Postoperative dietary data was pooled and re-classified into early postoperative dietary intake achievement (EDIA) (daily energy intake (DEI) ≥ 75% from the estimated energy requirement (EER)) and delay dietary intake achievement (DDIA) (DEI < 75% EER) There was a significant difference in postoperative changes in weight (p = 0.002), muscle mass (p = 0.018), and handgrip strength (p = 0.010) between the groups. Postoperative daily energy and protein intake in the EDIA was significantly greater than DDIA from operation day to discharged (p = 0.000 and p = 0.036). Four significant independent postoperative dietary intake predictors were found: preoperative whey protein-infused carbohydrate loading (p = 0.000), postoperative nausea vomiting (p = 0.001), age (p = 0.010), and time to tolerate clear fluid (p = 0.016). The multilinear regression model significantly predicted postoperative dietary intake, F (4, 116) = 68.013, p = 0.000, adj. R2 = 0.698. With the four predictors’ recognition, the integration of a more specific and comprehensive dietitian-led supportive care with individualized nutrition intervention ought to be considered to promote functional recovery.

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Veronese, Nicola, Ligia J. Dominguez, Saverio Ragusa, Luisa Solimando, Lee Smith, Francesco Bolzetta, Stefania Maggi, and Mario Barbagallo. "Dietary acrylamide and physical performance tests: A cross-sectional analysis." PLOS ONE 16, no. 11 (November 2, 2021): e0259320. http://dx.doi.org/10.1371/journal.pone.0259320.

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Background Dietary acrylamide is found in certain foods, such as deep frying, baking and roasting, and is associated with higher inflammatory and oxidative stress parameters. The association between dietary acrylamide and physical performance has not yet been explored. The aim of the study was to investigate the relationship between dietary acrylamide intake and physical performance tests in a large cohort of North American individuals affected by knee osteoarthritis or at high risk for this condition. Methods Dietary acrylamide intake was obtained through a food frequency questionnaire and reported in quartiles and as an increase in deciles. Physical performance was explored using the 20-meter usual pace test, the 400-meter walking distance, and the chair stands time. The association between dietary acrylamide and physical performance tests was explored using linear regression analysis, adjusted for potential confounders. Results 4,436 participants (2,578 women, mean age: 61.3) were enrolled. People in the highest quartile of dietary acrylamide reported significantly longer 20-meter walking (15.53±3.32 vs. 15.15±2.91 s), 400-meter walking (312±54 vs. 305±58 s) and chair stands (11.36±4.08 vs. 10.67±3.50 s) times than their counterparts in Q1. In adjusted linear regression analyses, each increase in one decile in dietary acrylamide was associated with a longer time in walking for 20 meters (beta = 0.032; 95%CI: 0.016–0.048; p = 0.04), 400 meters (beta = 0.048; 95%CI: 0.033–0.063; p = 0.002) and chair stands (beta = 0.016; 95%CI: 0.005–0.037; p = 0.04) times. Conclusion Higher dietary acrylamide intake was significantly associated with poor physical performance, also after accounting for potential confounders, suggesting a role for this food contaminant as a possible risk factor for sarcopenia.

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Reidlinger, Dianne P., Thomas AB Sanders, and Louise M. Goff. "How expensive is a cardioprotective diet? Analysis from the CRESSIDA study." Public Health Nutrition 20, no. 8 (January 18, 2017): 1423–30. http://dx.doi.org/10.1017/s1368980016003529.

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AbstractObjectiveTo determine whether a cardioprotective dietary intervention based on UK dietary guidelines was more expensive than a conventional UK diet.DesignCost analysis of food records collected at baseline and after a 12-week dietary intervention of a cardioprotective diet v. conventional UK diet.SettingA randomized controlled dietary intervention study (CRESSIDA; ISRCTN 92382106) investigating the impact of following a diet consistent with UK dietary guidelines on CVD risk.SubjectsParticipants were healthy UK residents aged 40–70 years. A sub-sample of participants was randomly selected from those who completed the cardioprotective dietary intervention (n 20) or the conventional UK dietary intervention (n 20).ResultsBaseline diet costs did not differ between groups; mean daily food cost for all participants was £6·12 (sd £1·83). The intervention diets were not more expensive: at end point the mean daily cost of the cardioprotective diet was £6·43 (sd £2·05) v. the control diet which was £6·53 (sd £1·53; P=0·86).ConclusionsThere was no evidence that consumption of a cardioprotective diet was more expensive than a conventional dietary pattern. Despite the perception that healthier foods are less affordable, these results suggest that cost may not be a barrier when modifying habitual intake and under tightly controlled trial conditions. The identification of specific food groups that may be a cost concern for individuals may be useful for tailoring interventions for CVD prevention for individuals and populations.

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Sharpless, Katherine E., and David L. Duewer. "Standard Reference Materials for Analysis of Dietary Supplements." Journal of AOAC INTERNATIONAL 91, no. 6 (November 1, 2008): 1298–302. http://dx.doi.org/10.1093/jaoac/91.6.1298.

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Abstract National Institute of Standards and Technology (NIST), in collaboration with the National Institutes of HealthOffice of Dietary Supplements and the U.S. Food and Drug Administration, is producing Standard Reference Materials (SRMs) for dietary supplements. These and other natural-matrix SRMs should be used in method validation, characterization of in-house quality control materials, and to establish traceability.

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