Protein

WP_Query Object
(
    [query] => Array
        (
            [post_type] => event
            [posts_per_page] => 5
            [type] => 
            [area] => 
            [before] => 2023-06-08
            [after] => 
            [tags] => protein
            [showtitle] => false
            [meta_query] => Array
                (
                    [relation] => AND
                    [0] => Array
                        (
                            [key] => _ilsi_date
                            [value] => 2018-06-08
                            [compare] => >=
                            [type] => DATE
                        )

                )

            [maxyears] => 5
            [paged] => 1
            [tax_query] => Array
                (
                    [0] => Array
                        (
                            [taxonomy] => post_tag
                            [field] => name
                            [terms] => protein
                        )

                )

            [meta_key] => _ilsi_date
            [orderby] => meta_value
            [order] => DESC
        )

    [query_vars] => Array
        (
            [post_type] => event
            [posts_per_page] => 5
            [type] => 
            [area] => 
            [before] => 2023-06-08
            [after] => 
            [tags] => protein
            [showtitle] => false
            [meta_query] => Array
                (
                    [relation] => AND
                    [0] => Array
                        (
                            [key] => _ilsi_date
                            [value] => 2018-06-08
                            [compare] => >=
                            [type] => DATE
                        )

                )

            [maxyears] => 5
            [paged] => 1
            [tax_query] => Array
                (
                    [0] => Array
                        (
                            [taxonomy] => post_tag
                            [field] => name
                            [terms] => protein
                        )

                )

            [meta_key] => _ilsi_date
            [orderby] => meta_value
            [order] => DESC
            [error] => 
            [m] => 
            [p] => 0
            [post_parent] => 
            [subpost] => 
            [subpost_id] => 
            [attachment] => 
            [attachment_id] => 0
            [name] => 
            [pagename] => 
            [page_id] => 0
            [second] => 
            [minute] => 
            [hour] => 
            [day] => 0
            [monthnum] => 0
            [year] => 0
            [w] => 0
            [category_name] => 
            [tag] => 
            [cat] => 
            [tag_id] => 194
            [author] => 
            [author_name] => 
            [feed] => 
            [tb] => 
            [meta_value] => 
            [preview] => 
            [s] => 
            [sentence] => 
            [title] => 
            [fields] => 
            [menu_order] => 
             => 
            [category__in] => Array
                (
                )

            [category__not_in] => Array
                (
                )

            [category__and] => Array
                (
                )

            [post__in] => Array
                (
                )

            [post__not_in] => Array
                (
                )

            [post_name__in] => Array
                (
                )

            [tag__in] => Array
                (
                )

            [tag__not_in] => Array
                (
                )

            [tag__and] => Array
                (
                )

            [tag_slug__in] => Array
                (
                )

            [tag_slug__and] => Array
                (
                )

            [post_parent__in] => Array
                (
                )

            [post_parent__not_in] => Array
                (
                )

            [author__in] => Array
                (
                )

            [author__not_in] => Array
                (
                )

            [ignore_sticky_posts] => 
            [suppress_filters] => 
            [cache_results] => 1
            [update_post_term_cache] => 1
            [update_menu_item_cache] => 
            [lazy_load_term_meta] => 1
            [update_post_meta_cache] => 1
            [nopaging] => 
            [comments_per_page] => 50
            [no_found_rows] => 
        )

    [tax_query] => WP_Tax_Query Object
        (
            [queries] => Array
                (
                    [0] => Array
                        (
                            [taxonomy] => post_tag
                            [terms] => Array
                                (
                                    [0] => protein
                                )

                            [field] => name
                            [operator] => IN
                            [include_children] => 1
                        )

                )

            [relation] => AND
            [table_aliases:protected] => Array
                (
                    [0] => wp_term_relationships
                )

            [queried_terms] => Array
                (
                    [post_tag] => Array
                        (
                            [terms] => Array
                                (
                                    [0] => protein
                                )

                            [field] => name
                        )

                )

            [primary_table] => wp_posts
            [primary_id_column] => ID
        )

    [meta_query] => WP_Meta_Query Object
        (
            [queries] => Array
                (
                    [0] => Array
                        (
                            [key] => _ilsi_date
                        )

                    [1] => Array
                        (
                            [0] => Array
                                (
                                    [key] => _ilsi_date
                                    [value] => 2018-06-08
                                    [compare] => >=
                                    [type] => DATE
                                )

                            [relation] => OR
                        )

                    [relation] => AND
                )

            [relation] => AND
            [meta_table] => wp_postmeta
            [meta_id_column] => post_id
            [primary_table] => wp_posts
            [primary_id_column] => ID
            [table_aliases:protected] => Array
                (
                    [0] => wp_postmeta
                    [1] => mt1
                )

            [clauses:protected] => Array
                (
                    [wp_postmeta] => Array
                        (
                            [key] => _ilsi_date
                            [compare] => =
                            [compare_key] => =
                            [alias] => wp_postmeta
                            [cast] => CHAR
                        )

                    [mt1] => Array
                        (
                            [key] => _ilsi_date
                            [value] => 2018-06-08
                            [compare] => >=
                            [type] => DATE
                            [compare_key] => =
                            [alias] => mt1
                            [cast] => DATE
                        )

                )

            [has_or_relation:protected] => 
        )

    [date_query] => 
    [request] => 
					SELECT SQL_CALC_FOUND_ROWS  wp_posts.ID
					FROM wp_posts  LEFT JOIN wp_term_relationships ON (wp_posts.ID = wp_term_relationships.object_id) INNER JOIN wp_postmeta ON ( wp_posts.ID = wp_postmeta.post_id )  INNER JOIN wp_postmeta AS mt1 ON ( wp_posts.ID = mt1.post_id )
					WHERE 1=1  AND ( 
  wp_term_relationships.term_taxonomy_id IN (194)
) AND ( 
  wp_postmeta.meta_key = '_ilsi_date' 
  AND 
  ( 
    ( mt1.meta_key = '_ilsi_date' AND CAST(mt1.meta_value AS DATE) >= '2018-06-08' )
  )
) AND ((wp_posts.post_type = 'event' AND (wp_posts.post_status = 'publish' OR wp_posts.post_status = 'acf-disabled')))
					GROUP BY wp_posts.ID
					ORDER BY wp_postmeta.meta_value DESC
					LIMIT 0, 5
				
    [posts] => Array
        (
            [0] => WP_Post Object
                (
                    [ID] => 27922
                    [post_author] => 343
                    [post_date] => 2022-03-15 15:08:58
                    [post_date_gmt] => 2022-03-15 15:08:58
                    [post_content] => 

	
Join IAFNS at the American Society for Nutrition Annual meeting - NUTRITION 2022 - to learn about some of our funded projects.
					Diet-Related and Gut-Derived Metabolites and Health Outcomes: A Scoping Review: Abstract Presentation Number: PO24-19-22 
											Expand
					Presenting Author: Yuanxi Jia, Johns Hopkins University

Topical Area: Nutritional Microbiology/Microbiome

Supported by: IAFNS Gut Microbiome Committee

For more information, see here.
ABSTRACT
Objectives: To conduct a scoping review to map available evidence about the health impact of gut microbiota-derived metabolites in humans.
Methods: We searched PubMed and Embase for studies that assessed the health impact of gut microbiota-derived metabolites in humans. We included case-control studies, cross-sectional studies, cohort studies, and clinical trials. Any health condition was considered. Based on an initial prioritization phase informed by preliminary searching and expert input, we narrowed our scope to ten metabolites: deoxycholate or deoxycholic acid (DCA), lithocholate or lithocholic acid (LCA), glycolithocholate or glycolithocholic acid, glycodeoxycholate or glycodeoxycholic acid, tryptamine, putrescine, d-alanine, urolithins, N-acetylmannosamine, and phenylacetylglutamine. We used evidence mapping to identify evidence gaps and associations that may permit future systematic reviews. The screening was conducted in PICO Portal aided by artificial intelligence.
Results: Overall, for these 10 metabolites, we identified 352 studies with 168,072 participants. Most (326, 92.6%) were case-control studies, followed by cohort studies (14, 4.0%), clinical trials (8, 2.3%), and cross-sectional studies (6, 1.7%). Most studies assessed the following associations: DCA on hepatobiliary disorders (64 studies, 7,976 participants), colorectal cancer (19 studies, 7,461 participants), and other digestive disorders (27 studies, 2,463 participants); LCA on hepatobiliary disorders (34 studies, 4,297 participants), colorectal cancers (14 studies, 4,955 participants), and other digestive disorders (26 studies, 2,117 participants); putrescine on colorectal cancers (16 studies, 94,399 participants) and cancers excluding colorectal and hepatobiliary cancers (42 studies, 4,250 participants).
Conclusions: The association of gut microbiota-derived metabolites and human health is being examined in an increasing number of studies, most of which are case-control studies. As these metabolites hold considerable potential for elucidating microbiome-disease associations, there is a need to conduct more prospective studies including clinical trials. Moreover, systemic reviews are needed to characterize the metabolite-disease associations.
Funding Sources: Institute for the Advancement of Food and Nutrition Sciences (IAFNS)
					Relationship Between Exposure to Dietary Sweetness and Body Weight-Related Outcomes in Adults: An Evidence Map: Abstract Presentation Number: PO08-20-22
											Expand
					Presenting Author: Kelly A. Higgins, USDA, ARS

Topical Area: Dietary Patterns

Supported by: IAFNS Carbohydrates and Low- and No-Calorie Sweeteners Committees

For more information, see here. 
ABSTRACT
Objectives: An evidence map was conducted to characterize published research investigating dietary sweetness and body weight. The primary aim was to identify studies that investigate total dietary sweetness and body weight-related outcomes among healthy adults; the secondary aim was to map the evidence that investigates sugar, sweetener, or sweet food/beverage intake and body weight.
Methods: Using pre-registered search terms (https://osf.io/my7pb), 33,609 publications (duplicates removed) from PubMed, Cochrane Library, and Scopus were screened for inclusion. Eligible studies were cross-sectional studies, longitudinal cohort studies, case control studies, clinical trials, and systematic reviews conducted among adults (≥18 years) which investigated the associations between total dietary sweetness, sugar, sweetener (energetic or nonenergetic), or sweet food/beverage intake on body weight, body mass index, adiposity, and energy intake.
Results: A total of 824 eligible publications were identified. Two clinical trials and 5 cross-sectional studies investigated the associations between total dietary sweetness and a body weight-related outcome. An additional 630 publications were identified that investigated sugar, sweetener, or sweet food/beverage intake and body weight-related outcomes, including 225 clinical trials, 87 longitudinal cohort studies, and 298 cross-sectional studies. Ninety publications reported on dietary patterns that included sweet foods/beverages alongside other dietary components. Most studies (91%) did not measure the sweetness of the diet or individual foods consumed. Additionally, 97 systematic reviews that addressed relevant but different research questions related to sweetness exposure and body weight-related outcomes were identified.
Conclusions: While there is a breadth of evidence available from studies that investigate sugar, sweetener, and sweet food/beverage intake and body weight, there is limited evidence on the association between total dietary sweetness exposure and body weight.
Funding Sources: USDA Agricultural Research Service, Institute for the Advancement of Food and Nutrition Sciences
					Quality of Popular Diets in the United States: Abstract Presentation Number: PO08-09-22
											Expand
					Presenting Author: Zach Conrad, William & Mary

Topical Area: Dietary Patterns

Supported by: IAFNS Carbohydrates Committee

For more information, see here.
ABSTRACT
Objectives: 1) Evaluate the quality of popular diets in the US, and 2) model the effect of targeted food substitutions on diet quality.
Methods: Dietary data from 34,411 adults ≥20 y were acquired from the National Health and Nutrition Examination Survey, 2005-2018. Usual dietary intake was assessed using the National Cancer Institute's usual intake methodology, and the Healthy Eating Index-2015 was used to evaluate the diet quality of eleven popular diets. A diet model was used to evaluate the effect of targeted food substitutions on diet quality.
Results: Participants that followed a pescatarian diet pattern had the highest diet quality (65.2, 95% CI: 64.0-66.4), followed by vegetarian (63.0, 62.0-63.0), very low grain (62.7, 62.2-63.3), flexible paleo (62.3, 61.1-63.4), low grain (61.2, 60.6-61.9), low-moderate grain (59.7, 59.3-60.2), omnivorous (57.8, 57.5-58.1), restricted carbohydrate (56.9, 56.6-57.3), time restricted (55.2, 54.8-55.5), moderate protein (55.0, 54.7-55.3), and high protein (51.8, 51.0-62.7). Modeled replacement of up to three daily servings of foods highest in added sugar, sodium, and saturated fat with alternative foods led to a statistically significant increase in diet quality and a decrease in energy intake for most diets (P < 0.001 for most diets).
Conclusions: Low diet quality was observed for all popular diets evaluated in this study. Modeled dietary shifts that align with recommendations to choose foods lower in added sugar, sodium, and saturated fat led to only modest improvements in diet quality but a larger reduction in energy intake. Greater efforts are needed to shift consumer perceptions away from reductionist dietary approaches that place undue emphasis on specific foods, individual macronutrients, and timing of eating, and toward healthy dietary patterns that emphasize consumption of a variety of high-quality food groups.
Funding Sources: This work was supported by the Institute for the Advancement of Food and Nutrition Sciences (IAFNS) Carbohydrate Committee. IAFNS is a nonprofit science organization that pools funding from industry collaborators and advances science through the in-kind and financial contributions from public and private sector participants. IAFNS had no role in the design, analysis, interpretation, or presentation of the data and results.
					Association Between Restricted Carbohydrate Diets and Cardiometabolic Disease: Abstract Presentation Number: PO22-26-22
											Expand
					Presenting Author: Corina Kowalski, William & Mary

Topical Area: Nutritional Epidemiology

Supported by: IAFNS Carbohydrate and Lipids Committees 

For more information, see here.
ABSTRACT
Objectives: This study evaluated the association between restricted carbohydrate diets and prevalent cardiometabolic disease (CMD), stratified by fat intake.
Methods: Dietary and CMD data were obtained from 19,078 participants ≥20 y in the National Health and Nutrition Examination Survey (NHANES) 1999-2018. The National Cancer Institute (NCI) methodology was used to assess usual intake of foods and nutrients.
Results: Compared to individuals that met all macronutrient recommendations, those consuming restricted carbohydrate diets ( < 45%en) were 1.123 (95% CI 1.113-1.133) times as likely to have CMD, and those consuming the recommended amount of carbohydrates only were 1.060 (1.058-1.062) times as likely to have CMD. Higher intakes of saturated and polyunsaturated fat were associated with greater prevalence of CMD in restricted and recommended carbohydrate intake groups. Higher intakes of monounsaturated fat were associated with lower prevalence of CMD among participants that met carbohydrate recommendations only.
Conclusions: Participants that consumed restricted carbohydrate diets were more likely to have CMD compared to participants that met all macronutrient recommendations, and this association was modified by fat intake. Greater efforts are needed to understand longitudinal associations between carbohydrate intake and CMD.
Funding Sources: This work was supported by the Institute for the Advancement of Food and Nutrition Sciences (IAFNS) Carbohydrate and Lipid Committees. IAFNS is a nonprofit science organization that pools funding from industry collaborators and advances science through the in-kind and financial contributions from public and private sector participants. IAFNS had no role in the design, analysis, interpretation, or presentation of the data and results.
					Restricted Carbohydrate Diets High in Fat Are Associated With Increased Likelihood of Prevalent Metabolic Syndrome: Abstract Presentation Number: PO22-13-22
											Expand
					Presenting Author: Dakota Dustin, The Ohio State University

Topical Area: Nutritional Epidemiology

Supported by: IAFNS Carbohydrate and Lipids Committees

For more information, see here.
ABSTRACT
Objectives: This study evaluated the association between a restricted carbohydrate diet ( < 45% energy from carbohydrate) and metabolic syndrome stratified by fatty acid classes in a nationally representative sample of U.S adults.
Methods: Data on food and nutrient intake, and markers of metabolic syndrome, were obtained from 19,078 respondents ≥20 y in the National Health and Nutrition Examination Survey (NHANES) 1999-2018. The National Cancer Institute's usual intake methodology was used to evaluate the associations between usual dietary intake and prevalent metabolic syndrome.
Results: Compared to individuals that met all AMDR macronutrient recommendations, the odds of having metabolic syndrome were 1.085 (95%CI: 1.077-1.094) times higher among those that consumed a restricted carbohydrate diet (P < 0.001) and 1.115 (1.153-1.156) times higher for those that met only current recommendations for total carbohydrates (P < 0.001). Higher fat intake, regardless of class, was associated with increased likelihood of metabolic syndrome among individuals that consumed restricted carbohydrate diets but not among individuals that met current carbohydrate recommendations.
Conclusions: The likelihood of prevalent metabolic syndrome was moderately higher (8.5%) among individuals that consumed restricted carbohydrate diets compared to individuals that met all macronutrient recommendations. High intake of fat of any class was associated with increased likelihood of metabolic syndrome in those consuming a restricted carbohydrate diet.
Funding Sources: This work was supported by the Institute for the Advancement of Food and Nutrition Sciences (IAFNS) Carbohydrate and Lipid Committees. IAFNS is a nonprofit science organization that pools funding from industry collaborators and advances science through the in-kind and financial contributions from public and private sector participants. IAFNS had no role in the design, analysis, interpretation, or presentation of the data and results.
 
					Associations Between Essential Amino Acids and Functional Health Outcomes in Older Adults: Analysis of the National Health and Nutrition Examination Survey, 2001-2018:Abstract Presentation Number: PO22-09-22
											Expand
					Abstract Topical Area: Nutritional Epidemiology, FSU Metabolic Kitchen & Diet Assessment Center

Presenting Author: Susan Cheung

Supported by: IAFNS Protein Committee

For more information, see here.
ABSTRACT:
Objectives: Little is known about the relationships between habitual essential amino acid (EAA) intake and functional health in older US adults. This cross-sectional study investigates associations between usual EAA intakes and body composition, muscle strength, and physical function in US adults ≥ 65 y.
Methods: The Food and Nutrient Database for Dietary Studies (FNDDS) 2001-2018 was linked to USDA FoodData Central to access existing EAA composition data for FNDDS ingredients. FNDDS ingredients without existing EAA data were matched to similar ingredient codes with available EAA data. Usual intakes of EAA, leucine, lysine, and sulfur-containing AAs (SAA; methionine + cysteine) from NHANES 2001-2018 were calculated as relative [mg/kg ideal body weight (IBW)/d] and absolute (g/d) intakes for individuals ≥ 65 y (n=10,843). Dependent variables were muscle strength measured by isometric grip test, BMI, waist circumference (WC), DXA-measured appendicular lean mass and whole-body fat mass, and self-reported physical function. Regression analyses were used to determine covariate-adjusted relationships between EAA, leucine, lysine, and SAA intake and functional health outcomes. P < 0.0013 was considered significant.
Results: Absolute and relative EAA, leucine, lysine, and SAA intakes were not associated with muscle strength or self-reported physical function in males or females or with body composition in males. Absolute EAA intakes (per g) were associated with WC in females (β ± SEM, 2.1 ± 0.6 cm, P = 0.0007). Absolute lysine intakes (per g) were associated with BMI (3.0 ± 0.7 kg/m2, P < 0.0001) and WC (7.0 ± 1.7 cm, P = 0.0001) in females. Relative EAA, leucine, and lysine intakes (per mg/kg IBW) were associated with BMI (0.07 ± 0.02, 0.26 ± 0.07, and 0.25 ± 0.04 kg/m2, respectively; P ≤ 0.0004 for all) and WC (0.18 ± 0.03, 0.81 ± 0.17, and 0.64 ± 0.10 cm, respectively; P < 0.0001 for all) in females. Relative lysine intakes (per mg/kg IBW) were associated with whole body fat mass (0.24 ± 0.07 kg, P = 0.0006) in females.
Conclusions: EAA intakes, particularly lysine, were positively associated with measures of adiposity in women ≥ 65 y. Investigating sources of lysine intake may provide insight about which foods or food groups are driving this relationship.
Funding Sources: IAFNS Protein Committee, USAMRDC, DoD Center Alliance for Nutrition and Dietary Supplements Research
					Amino Acid Intake and Conformance With the Dietary Reference Intakes in the United States: Analysis of the National Health and Nutrition Examination Survey, 2001-2018: Abstract Presentation Number: PO22-06-22
											Expand
					Abstract Topical Area: Nutritional Epidemiology

Presenting Author: Claire Berryman, Florida State University

Supported by: IAFNS Protein Committee

For more information, see here.
ABSTRACT

Objectives: The lack of complete amino acid composition data in food composition databases has made determining population-wide amino acid intake difficult. This cross-sectional study characterizes habitual intakes of each amino acid and adherence to dietary requirements for each essential amino acid (EAA) by age, gender, and race/ethnicity in the US population.
Methods: Food and Nutrient Database for Dietary Studies ingredient codes with missing amino acid composition data were matched to similar ingredients with available data, so that amino acid composition could be determined for virtually 100% of foods reported in What We Eat in America, the dietary intake assessment component of NHANES. Amino acid intakes during 2-y cycles of NHANES 2001-2018 (n = 84,629; ≥ 2y) were calculated as relative [mg/kg of ideal body weight (IBW)/d] and absolute (g/d) intakes. Data from NHANES 2011-2018 were used to determine the percentage of the population consuming less than the Dietary Reference Intakes for each EAA by age, sex, and race/ethnicity.
Results: Relative intakes of EAAs were greatest in those 2-3 y (females: 1552 ± 9 and males: 1659 ± 9 mg/kg IBW/d) and lowest in those ≥ 80 y (females: 446 ± 2 and males: 461 ± 3 mg/kg IBW/d). Absolute intakes of EAAs were greatest in those 31-50 y (females: 31.4 ± 0.1 and males: 45.5 ± 0.1 g/d) and lowest in those 2-3 y (females: 22.4 ± 0.1 and males: 26.0 ± 0.1 g/d). In individuals 2-18 y and ≥ 19 y, relative intakes of EAAs were lowest in the NHB population (860 ± 16 and 505 ± 5 mg/kg IBW/d, respectively) and highest in the Asian population (994 ± 35 and 580 ± 7 mg/kg IBW/d, respectively). Less than 1% of individuals ≥ 19 y were not meeting the Estimated Average Requirements for each EAA.
Conclusions: Individual amino acid intakes in the US population exceed recommended minimum population requirements. Future studies can use the method described here to quantify habitual amino acid intake and examine relationships with health and disease.
Funding Sources: Institute for the Advancement of Food and Nutrition Sciences (IAFNS) Protein Committee, US Army Medical Research and Development Command, and the Department of Defense Center Alliance for Nutrition and Dietary Supplements Research.


                    [post_title] => IAFNS at NUTRITION 2022
                    [post_excerpt] => 
                    [post_status] => publish
                    [comment_status] => closed
                    [ping_status] => closed
                    [post_password] => 
                    [post_name] => iafns-at-nutrition-2022
                    [to_ping] => 
                    [pinged] => 
                    [post_modified] => 2023-05-02 11:10:08
                    [post_modified_gmt] => 2023-05-02 15:10:08
                    [post_content_filtered] => 
                    [post_parent] => 0
                    [guid] => https://iafns.org/?post_type=event&p=27922
                    [menu_order] => 0
                    [post_type] => event
                    [post_mime_type] => 
                    [comment_count] => 0
                    [filter] => raw
                )

        )

    [post_count] => 1
    [current_post] => -1
    [in_the_loop] => 
    [post] => WP_Post Object
        (
            [ID] => 27922
            [post_author] => 343
            [post_date] => 2022-03-15 15:08:58
            [post_date_gmt] => 2022-03-15 15:08:58
            [post_content] => 

	
Join IAFNS at the American Society for Nutrition Annual meeting - NUTRITION 2022 - to learn about some of our funded projects.
					Diet-Related and Gut-Derived Metabolites and Health Outcomes: A Scoping Review: Abstract Presentation Number: PO24-19-22 
											Expand
					Presenting Author: Yuanxi Jia, Johns Hopkins University

Topical Area: Nutritional Microbiology/Microbiome

Supported by: IAFNS Gut Microbiome Committee

For more information, see here.
ABSTRACT
Objectives: To conduct a scoping review to map available evidence about the health impact of gut microbiota-derived metabolites in humans.
Methods: We searched PubMed and Embase for studies that assessed the health impact of gut microbiota-derived metabolites in humans. We included case-control studies, cross-sectional studies, cohort studies, and clinical trials. Any health condition was considered. Based on an initial prioritization phase informed by preliminary searching and expert input, we narrowed our scope to ten metabolites: deoxycholate or deoxycholic acid (DCA), lithocholate or lithocholic acid (LCA), glycolithocholate or glycolithocholic acid, glycodeoxycholate or glycodeoxycholic acid, tryptamine, putrescine, d-alanine, urolithins, N-acetylmannosamine, and phenylacetylglutamine. We used evidence mapping to identify evidence gaps and associations that may permit future systematic reviews. The screening was conducted in PICO Portal aided by artificial intelligence.
Results: Overall, for these 10 metabolites, we identified 352 studies with 168,072 participants. Most (326, 92.6%) were case-control studies, followed by cohort studies (14, 4.0%), clinical trials (8, 2.3%), and cross-sectional studies (6, 1.7%). Most studies assessed the following associations: DCA on hepatobiliary disorders (64 studies, 7,976 participants), colorectal cancer (19 studies, 7,461 participants), and other digestive disorders (27 studies, 2,463 participants); LCA on hepatobiliary disorders (34 studies, 4,297 participants), colorectal cancers (14 studies, 4,955 participants), and other digestive disorders (26 studies, 2,117 participants); putrescine on colorectal cancers (16 studies, 94,399 participants) and cancers excluding colorectal and hepatobiliary cancers (42 studies, 4,250 participants).
Conclusions: The association of gut microbiota-derived metabolites and human health is being examined in an increasing number of studies, most of which are case-control studies. As these metabolites hold considerable potential for elucidating microbiome-disease associations, there is a need to conduct more prospective studies including clinical trials. Moreover, systemic reviews are needed to characterize the metabolite-disease associations.
Funding Sources: Institute for the Advancement of Food and Nutrition Sciences (IAFNS)
					Relationship Between Exposure to Dietary Sweetness and Body Weight-Related Outcomes in Adults: An Evidence Map: Abstract Presentation Number: PO08-20-22
											Expand
					Presenting Author: Kelly A. Higgins, USDA, ARS

Topical Area: Dietary Patterns

Supported by: IAFNS Carbohydrates and Low- and No-Calorie Sweeteners Committees

For more information, see here. 
ABSTRACT
Objectives: An evidence map was conducted to characterize published research investigating dietary sweetness and body weight. The primary aim was to identify studies that investigate total dietary sweetness and body weight-related outcomes among healthy adults; the secondary aim was to map the evidence that investigates sugar, sweetener, or sweet food/beverage intake and body weight.
Methods: Using pre-registered search terms (https://osf.io/my7pb), 33,609 publications (duplicates removed) from PubMed, Cochrane Library, and Scopus were screened for inclusion. Eligible studies were cross-sectional studies, longitudinal cohort studies, case control studies, clinical trials, and systematic reviews conducted among adults (≥18 years) which investigated the associations between total dietary sweetness, sugar, sweetener (energetic or nonenergetic), or sweet food/beverage intake on body weight, body mass index, adiposity, and energy intake.
Results: A total of 824 eligible publications were identified. Two clinical trials and 5 cross-sectional studies investigated the associations between total dietary sweetness and a body weight-related outcome. An additional 630 publications were identified that investigated sugar, sweetener, or sweet food/beverage intake and body weight-related outcomes, including 225 clinical trials, 87 longitudinal cohort studies, and 298 cross-sectional studies. Ninety publications reported on dietary patterns that included sweet foods/beverages alongside other dietary components. Most studies (91%) did not measure the sweetness of the diet or individual foods consumed. Additionally, 97 systematic reviews that addressed relevant but different research questions related to sweetness exposure and body weight-related outcomes were identified.
Conclusions: While there is a breadth of evidence available from studies that investigate sugar, sweetener, and sweet food/beverage intake and body weight, there is limited evidence on the association between total dietary sweetness exposure and body weight.
Funding Sources: USDA Agricultural Research Service, Institute for the Advancement of Food and Nutrition Sciences
					Quality of Popular Diets in the United States: Abstract Presentation Number: PO08-09-22
											Expand
					Presenting Author: Zach Conrad, William & Mary

Topical Area: Dietary Patterns

Supported by: IAFNS Carbohydrates Committee

For more information, see here.
ABSTRACT
Objectives: 1) Evaluate the quality of popular diets in the US, and 2) model the effect of targeted food substitutions on diet quality.
Methods: Dietary data from 34,411 adults ≥20 y were acquired from the National Health and Nutrition Examination Survey, 2005-2018. Usual dietary intake was assessed using the National Cancer Institute's usual intake methodology, and the Healthy Eating Index-2015 was used to evaluate the diet quality of eleven popular diets. A diet model was used to evaluate the effect of targeted food substitutions on diet quality.
Results: Participants that followed a pescatarian diet pattern had the highest diet quality (65.2, 95% CI: 64.0-66.4), followed by vegetarian (63.0, 62.0-63.0), very low grain (62.7, 62.2-63.3), flexible paleo (62.3, 61.1-63.4), low grain (61.2, 60.6-61.9), low-moderate grain (59.7, 59.3-60.2), omnivorous (57.8, 57.5-58.1), restricted carbohydrate (56.9, 56.6-57.3), time restricted (55.2, 54.8-55.5), moderate protein (55.0, 54.7-55.3), and high protein (51.8, 51.0-62.7). Modeled replacement of up to three daily servings of foods highest in added sugar, sodium, and saturated fat with alternative foods led to a statistically significant increase in diet quality and a decrease in energy intake for most diets (P < 0.001 for most diets).
Conclusions: Low diet quality was observed for all popular diets evaluated in this study. Modeled dietary shifts that align with recommendations to choose foods lower in added sugar, sodium, and saturated fat led to only modest improvements in diet quality but a larger reduction in energy intake. Greater efforts are needed to shift consumer perceptions away from reductionist dietary approaches that place undue emphasis on specific foods, individual macronutrients, and timing of eating, and toward healthy dietary patterns that emphasize consumption of a variety of high-quality food groups.
Funding Sources: This work was supported by the Institute for the Advancement of Food and Nutrition Sciences (IAFNS) Carbohydrate Committee. IAFNS is a nonprofit science organization that pools funding from industry collaborators and advances science through the in-kind and financial contributions from public and private sector participants. IAFNS had no role in the design, analysis, interpretation, or presentation of the data and results.
					Association Between Restricted Carbohydrate Diets and Cardiometabolic Disease: Abstract Presentation Number: PO22-26-22
											Expand
					Presenting Author: Corina Kowalski, William & Mary

Topical Area: Nutritional Epidemiology

Supported by: IAFNS Carbohydrate and Lipids Committees 

For more information, see here.
ABSTRACT
Objectives: This study evaluated the association between restricted carbohydrate diets and prevalent cardiometabolic disease (CMD), stratified by fat intake.
Methods: Dietary and CMD data were obtained from 19,078 participants ≥20 y in the National Health and Nutrition Examination Survey (NHANES) 1999-2018. The National Cancer Institute (NCI) methodology was used to assess usual intake of foods and nutrients.
Results: Compared to individuals that met all macronutrient recommendations, those consuming restricted carbohydrate diets ( < 45%en) were 1.123 (95% CI 1.113-1.133) times as likely to have CMD, and those consuming the recommended amount of carbohydrates only were 1.060 (1.058-1.062) times as likely to have CMD. Higher intakes of saturated and polyunsaturated fat were associated with greater prevalence of CMD in restricted and recommended carbohydrate intake groups. Higher intakes of monounsaturated fat were associated with lower prevalence of CMD among participants that met carbohydrate recommendations only.
Conclusions: Participants that consumed restricted carbohydrate diets were more likely to have CMD compared to participants that met all macronutrient recommendations, and this association was modified by fat intake. Greater efforts are needed to understand longitudinal associations between carbohydrate intake and CMD.
Funding Sources: This work was supported by the Institute for the Advancement of Food and Nutrition Sciences (IAFNS) Carbohydrate and Lipid Committees. IAFNS is a nonprofit science organization that pools funding from industry collaborators and advances science through the in-kind and financial contributions from public and private sector participants. IAFNS had no role in the design, analysis, interpretation, or presentation of the data and results.
					Restricted Carbohydrate Diets High in Fat Are Associated With Increased Likelihood of Prevalent Metabolic Syndrome: Abstract Presentation Number: PO22-13-22
											Expand
					Presenting Author: Dakota Dustin, The Ohio State University

Topical Area: Nutritional Epidemiology

Supported by: IAFNS Carbohydrate and Lipids Committees

For more information, see here.
ABSTRACT
Objectives: This study evaluated the association between a restricted carbohydrate diet ( < 45% energy from carbohydrate) and metabolic syndrome stratified by fatty acid classes in a nationally representative sample of U.S adults.
Methods: Data on food and nutrient intake, and markers of metabolic syndrome, were obtained from 19,078 respondents ≥20 y in the National Health and Nutrition Examination Survey (NHANES) 1999-2018. The National Cancer Institute's usual intake methodology was used to evaluate the associations between usual dietary intake and prevalent metabolic syndrome.
Results: Compared to individuals that met all AMDR macronutrient recommendations, the odds of having metabolic syndrome were 1.085 (95%CI: 1.077-1.094) times higher among those that consumed a restricted carbohydrate diet (P < 0.001) and 1.115 (1.153-1.156) times higher for those that met only current recommendations for total carbohydrates (P < 0.001). Higher fat intake, regardless of class, was associated with increased likelihood of metabolic syndrome among individuals that consumed restricted carbohydrate diets but not among individuals that met current carbohydrate recommendations.
Conclusions: The likelihood of prevalent metabolic syndrome was moderately higher (8.5%) among individuals that consumed restricted carbohydrate diets compared to individuals that met all macronutrient recommendations. High intake of fat of any class was associated with increased likelihood of metabolic syndrome in those consuming a restricted carbohydrate diet.
Funding Sources: This work was supported by the Institute for the Advancement of Food and Nutrition Sciences (IAFNS) Carbohydrate and Lipid Committees. IAFNS is a nonprofit science organization that pools funding from industry collaborators and advances science through the in-kind and financial contributions from public and private sector participants. IAFNS had no role in the design, analysis, interpretation, or presentation of the data and results.
 
					Associations Between Essential Amino Acids and Functional Health Outcomes in Older Adults: Analysis of the National Health and Nutrition Examination Survey, 2001-2018:Abstract Presentation Number: PO22-09-22
											Expand
					Abstract Topical Area: Nutritional Epidemiology, FSU Metabolic Kitchen & Diet Assessment Center

Presenting Author: Susan Cheung

Supported by: IAFNS Protein Committee

For more information, see here.
ABSTRACT:
Objectives: Little is known about the relationships between habitual essential amino acid (EAA) intake and functional health in older US adults. This cross-sectional study investigates associations between usual EAA intakes and body composition, muscle strength, and physical function in US adults ≥ 65 y.
Methods: The Food and Nutrient Database for Dietary Studies (FNDDS) 2001-2018 was linked to USDA FoodData Central to access existing EAA composition data for FNDDS ingredients. FNDDS ingredients without existing EAA data were matched to similar ingredient codes with available EAA data. Usual intakes of EAA, leucine, lysine, and sulfur-containing AAs (SAA; methionine + cysteine) from NHANES 2001-2018 were calculated as relative [mg/kg ideal body weight (IBW)/d] and absolute (g/d) intakes for individuals ≥ 65 y (n=10,843). Dependent variables were muscle strength measured by isometric grip test, BMI, waist circumference (WC), DXA-measured appendicular lean mass and whole-body fat mass, and self-reported physical function. Regression analyses were used to determine covariate-adjusted relationships between EAA, leucine, lysine, and SAA intake and functional health outcomes. P < 0.0013 was considered significant.
Results: Absolute and relative EAA, leucine, lysine, and SAA intakes were not associated with muscle strength or self-reported physical function in males or females or with body composition in males. Absolute EAA intakes (per g) were associated with WC in females (β ± SEM, 2.1 ± 0.6 cm, P = 0.0007). Absolute lysine intakes (per g) were associated with BMI (3.0 ± 0.7 kg/m2, P < 0.0001) and WC (7.0 ± 1.7 cm, P = 0.0001) in females. Relative EAA, leucine, and lysine intakes (per mg/kg IBW) were associated with BMI (0.07 ± 0.02, 0.26 ± 0.07, and 0.25 ± 0.04 kg/m2, respectively; P ≤ 0.0004 for all) and WC (0.18 ± 0.03, 0.81 ± 0.17, and 0.64 ± 0.10 cm, respectively; P < 0.0001 for all) in females. Relative lysine intakes (per mg/kg IBW) were associated with whole body fat mass (0.24 ± 0.07 kg, P = 0.0006) in females.
Conclusions: EAA intakes, particularly lysine, were positively associated with measures of adiposity in women ≥ 65 y. Investigating sources of lysine intake may provide insight about which foods or food groups are driving this relationship.
Funding Sources: IAFNS Protein Committee, USAMRDC, DoD Center Alliance for Nutrition and Dietary Supplements Research
					Amino Acid Intake and Conformance With the Dietary Reference Intakes in the United States: Analysis of the National Health and Nutrition Examination Survey, 2001-2018: Abstract Presentation Number: PO22-06-22
											Expand
					Abstract Topical Area: Nutritional Epidemiology

Presenting Author: Claire Berryman, Florida State University

Supported by: IAFNS Protein Committee

For more information, see here.
ABSTRACT

Objectives: The lack of complete amino acid composition data in food composition databases has made determining population-wide amino acid intake difficult. This cross-sectional study characterizes habitual intakes of each amino acid and adherence to dietary requirements for each essential amino acid (EAA) by age, gender, and race/ethnicity in the US population.
Methods: Food and Nutrient Database for Dietary Studies ingredient codes with missing amino acid composition data were matched to similar ingredients with available data, so that amino acid composition could be determined for virtually 100% of foods reported in What We Eat in America, the dietary intake assessment component of NHANES. Amino acid intakes during 2-y cycles of NHANES 2001-2018 (n = 84,629; ≥ 2y) were calculated as relative [mg/kg of ideal body weight (IBW)/d] and absolute (g/d) intakes. Data from NHANES 2011-2018 were used to determine the percentage of the population consuming less than the Dietary Reference Intakes for each EAA by age, sex, and race/ethnicity.
Results: Relative intakes of EAAs were greatest in those 2-3 y (females: 1552 ± 9 and males: 1659 ± 9 mg/kg IBW/d) and lowest in those ≥ 80 y (females: 446 ± 2 and males: 461 ± 3 mg/kg IBW/d). Absolute intakes of EAAs were greatest in those 31-50 y (females: 31.4 ± 0.1 and males: 45.5 ± 0.1 g/d) and lowest in those 2-3 y (females: 22.4 ± 0.1 and males: 26.0 ± 0.1 g/d). In individuals 2-18 y and ≥ 19 y, relative intakes of EAAs were lowest in the NHB population (860 ± 16 and 505 ± 5 mg/kg IBW/d, respectively) and highest in the Asian population (994 ± 35 and 580 ± 7 mg/kg IBW/d, respectively). Less than 1% of individuals ≥ 19 y were not meeting the Estimated Average Requirements for each EAA.
Conclusions: Individual amino acid intakes in the US population exceed recommended minimum population requirements. Future studies can use the method described here to quantify habitual amino acid intake and examine relationships with health and disease.
Funding Sources: Institute for the Advancement of Food and Nutrition Sciences (IAFNS) Protein Committee, US Army Medical Research and Development Command, and the Department of Defense Center Alliance for Nutrition and Dietary Supplements Research.


            [post_title] => IAFNS at NUTRITION 2022
            [post_excerpt] => 
            [post_status] => publish
            [comment_status] => closed
            [ping_status] => closed
            [post_password] => 
            [post_name] => iafns-at-nutrition-2022
            [to_ping] => 
            [pinged] => 
            [post_modified] => 2023-05-02 11:10:08
            [post_modified_gmt] => 2023-05-02 15:10:08
            [post_content_filtered] => 
            [post_parent] => 0
            [guid] => https://iafns.org/?post_type=event&p=27922
            [menu_order] => 0
            [post_type] => event
            [post_mime_type] => 
            [comment_count] => 0
            [filter] => raw
        )

    [comment_count] => 0
    [current_comment] => -1
    [found_posts] => 1
    [max_num_pages] => 1
    [max_num_comment_pages] => 0
    [is_single] => 
    [is_preview] => 
    [is_page] => 
    [is_archive] => 1
    [is_date] => 
    [is_year] => 
    [is_month] => 
    [is_day] => 
    [is_time] => 
    [is_author] => 
    [is_category] => 
    [is_tag] => 1
    [is_tax] => 
    [is_search] => 
    [is_feed] => 
    [is_comment_feed] => 
    [is_trackback] => 
    [is_home] => 
    [is_privacy_policy] => 
    [is_404] => 
    [is_embed] => 
    [is_paged] => 
    [is_admin] => 
    [is_attachment] => 
    [is_singular] => 
    [is_robots] => 
    [is_favicon] => 
    [is_posts_page] => 
    [is_post_type_archive] => 
    [query_vars_hash:WP_Query:private] => 39b7010be9468fb6334cf00dcd4d3039
    [query_vars_changed:WP_Query:private] => 
    [thumbnails_cached] => 
    [allow_query_attachment_by_filename:protected] => 
    [stopwords:WP_Query:private] => 
    [compat_fields:WP_Query:private] => Array
        (
            [0] => query_vars_hash
            [1] => query_vars_changed
        )

    [compat_methods:WP_Query:private] => Array
        (
            [0] => init_query_flags
            [1] => parse_tax_query
        )

)