Study of Nutrition in Postpartum and Early Life Feeding Study

NCT ID: NCT06082921

Last Updated: 2024-12-16

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

24 participants

Study Classification

INTERVENTIONAL

Study Start Date

2023-10-18

Study Completion Date

2024-08-18

Brief Summary

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The first few months of life are a critical time for setting the health trajectory of both infants and mothers. It is essential that guidance provided to new families be based on the most rigorous scientific evidence available. Beef serves as a highly nutrient-rich option for lactating women. Plant-based beef products have similar nutrient profiles, and some consumers perceive them as a healthier alternative to traditional beef. This study aims to understand the different effects that beef and plant-based beef have on breastmilk composition, maternal glycemic control, maternal intake and satiety, and infant intake. Understanding the differences between beef and plant-based beef can help parents make informed decisions about optimal nutrition for their infants and themselves.

Detailed Description

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During the initial months of life, it is critical to set a path towards a healthy future for both the infant and mother.1-4 It is essential to provide new families with guidance that is grounded in the most rigorous scientific evidence possible. Although beef is a highly nutritious option for lactating women, there are now many plant-based beef products with similar nutrient profiles. Some consumers consider these substitutes to be a healthier alternative to beef. 5 "Plant-based" meat alternatives have become a common component of many Americans diets.5 A controlled trial is necessary to explore differences between beef and plant-based beef.

There have been no trials to establish differences in biochemical compounds available to breastfeeding infants in human milk based on lactating mothers' consumption of meat vs. plant-based meat. Furthermore, the amounts of compounds related to plant-based meat analogues that are transferred from a mother's diet into her breastmilk have also not been examined. While maternal weight status is increasingly linked to milk composition and differences in infant weight status,6-9 the role of diet in these associations has not been studied. These differences in breastmilk composition related to infant weight could explain inconsistent influence of breastfeeding on later weight status. Identifying possible biomarkers transferred from mothers to infants in breastmilk would elucidate potential biological mechanisms to explain the diet-weight relationship.

Finally, while some studies have linked metabolic dysregulation such as obesity or diabetes to negative alterations in breastmilk composition,3,7,10-13 we are not aware of any studies that consider whether the deleterious effects are attributable to glycemic control. Differences in ingredients and processing could lead to a differential effect on glycemic response in meat vs. plant-based meat.14-17 Such a finding would contribute to understanding the mechanisms by which maternal postnatal health and diet influence infant development.

This pilot study will help plan for future studies related to this population.

Conditions

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Glycemic Response Breast Feeding, Exclusive Eating Behavior

Keywords

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feeding trial breast milk postpartum fatty acids continuous glucose monitor beef plant-based meat

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

CROSSOVER

Primary Study Purpose

BASIC_SCIENCE

Blinding Strategy

SINGLE

Participants

Study Groups

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Beef Diet

Participants will eat 3 chef prepared meals a day that contain beef as main protein source. Snacks and desserts will be provided. All aspects of the meals, except for meat type (beef/impossible beef) will be the same during each arm. The base diet will be comprised of whole foods. Meals will meet acceptable macronutrient distribution ranges of the USDA.

Group Type EXPERIMENTAL

Beef Diet Intervention

Intervention Type BEHAVIORAL

Participants will eat prepared meals including beef for 6 days. Participants will eat a habitual diet for 6 days prior to intervention.

Impossible Beef Diet

Participants will eat 3 chef prepared meals a day that contain impossible beef as main protein source. Snacks and desserts will be provided. All aspects of the meals, except for meat type (beef/impossible beef) will be the same during each arm. The base diet will be comprised of whole foods. Meals will meet acceptable macronutrient distribution ranges of the USDA.

Group Type EXPERIMENTAL

Impossible Beef Diet Intervention

Intervention Type BEHAVIORAL

Participants will eat prepared meals including impossible beef for one portion 6 days. Participants will eat a habitual diet for 6 days prior to intervention.

Interventions

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Beef Diet Intervention

Participants will eat prepared meals including beef for 6 days. Participants will eat a habitual diet for 6 days prior to intervention.

Intervention Type BEHAVIORAL

Impossible Beef Diet Intervention

Participants will eat prepared meals including impossible beef for one portion 6 days. Participants will eat a habitual diet for 6 days prior to intervention.

Intervention Type BEHAVIORAL

Other Intervention Names

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Diet Intervention with Beef Diet Intervention with Impossible Beef

Eligibility Criteria

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Inclusion Criteria

1. Comfortable communicating in English, both orally and in writing
2. Infant aged between 6 and 12 weeks at enrollment
3. Exclusively breastfeeding one infant
4. Intention to continue breastfeeding through duration of the study
5. BMI between (18.5 - 29.9) OR BMI 30 - 35 and willing to consume an additional \~240 calories to ensure against caloric deficit
6. Willing to consume both meat \& plant-based meat products
7. Residing within \~10 mi radius of UT


1. Exclusively breastfeeding
2. Birth weight ≥ 2.5kg (5.5 lbs)

Exclusion Criteria

1. Pre-gestational diabetes, previous diagnosis of diabetes, or history of GDM (need specific diet)
2. Negative delivery outcome (post-delivery stillbirth, infant mortality)
3. Began complementary feeding or intends to begin feeding solid food before completion of study, infant age \<16 weeks.
4. Active eating disorder (atypical diet quality, anxiety about diet and weight/body measurements and weight gain)
5. Active substance abuse with alcohol or drugs by self-report (risk for poor adherence and could impact outcomes)
6. Treatment with medications (e.g., corticosteroids, anti-psychotics) known to have metabolic/body weight effects
7. BMI \<18.5 or \>35kg/m2
8. Unable or unwilling to follow protocol
9. Mom following vegetarian, vegan, or strict exclusion diet during pregnancy or lactation
10. Excessive caffeine consumer
11. Not a good candidate for a feeding trial (In general, if there are a variety of things indicating the potential participant might have a hard time meeting the requirements for the diet intervention. For example, if during screening, the potential participant indicates something that suggests they would be dishonest about their adherence to the diet.)


1. Preterm or in NICU post birth for \>72 hours
2. Low birth weight \< 2.5 kg
3. Negative health outcome following delivery that could affect breast feeding
Minimum Eligible Age

18 Years

Eligible Sex

FEMALE

Accepts Healthy Volunteers

No

Sponsors

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University of Texas at Austin

OTHER

Sponsor Role lead

National Cattlemen's Beef Association

INDUSTRY

Sponsor Role collaborator

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Marissa Burgermaster, PhD

Role: PRINCIPAL_INVESTIGATOR

University of Texas at Austin

Tom Brenna, PhD

Role: PRINCIPAL_INVESTIGATOR

University of Texas at Austin

Locations

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University of Texas at Austin - Burgermaster Lab

Austin, Texas, United States

Site Status

Countries

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United States

References

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Tinius RA, Yoho K, Blankenship MM, Maples JM. Postpartum Metabolism: How Does It Change from Pregnancy and What are the Potential Implications? Int J Womens Health. 2021 Jun 17;13:591-599. doi: 10.2147/IJWH.S314469. eCollection 2021.

Reference Type BACKGROUND
PMID: 34168507 (View on PubMed)

Marshall NE, Abrams B, Barbour LA, Catalano P, Christian P, Friedman JE, Hay WW Jr, Hernandez TL, Krebs NF, Oken E, Purnell JQ, Roberts JM, Soltani H, Wallace J, Thornburg KL. The importance of nutrition in pregnancy and lactation: lifelong consequences. Am J Obstet Gynecol. 2022 May;226(5):607-632. doi: 10.1016/j.ajog.2021.12.035. Epub 2021 Dec 27.

Reference Type BACKGROUND
PMID: 34968458 (View on PubMed)

Choi E, Kazzi B, Varma B, Ortengren AR, Minhas AS, Vaught AJ, Bennett WL, Lewey J, Michos ED. The Fourth Trimester: a Time for Enhancing Transitions in Cardiovascular Care. Curr Cardiovasc Risk Rep. 2022;16(12):219-229. doi: 10.1007/s12170-022-00706-x. Epub 2022 Sep 21.

Reference Type BACKGROUND
PMID: 36159207 (View on PubMed)

Gunderson EP. Childbearing and obesity in women: weight before, during, and after pregnancy. Obstet Gynecol Clin North Am. 2009 Jun;36(2):317-32, ix. doi: 10.1016/j.ogc.2009.04.001.

Reference Type BACKGROUND
PMID: 19501316 (View on PubMed)

Ley SH, Hanley AJ, Sermer M, Zinman B, O'Connor DL. Associations of prenatal metabolic abnormalities with insulin and adiponectin concentrations in human milk. Am J Clin Nutr. 2012 Apr;95(4):867-74. doi: 10.3945/ajcn.111.028431. Epub 2012 Feb 29.

Reference Type BACKGROUND
PMID: 22378730 (View on PubMed)

Young BE, Levek C, Reynolds RM, Rudolph MC, MacLean P, Hernandez TL, Friedman JE, Krebs NF. Bioactive components in human milk are differentially associated with rates of lean and fat mass deposition in infants of mothers with normal vs. elevated BMI. Pediatr Obes. 2018 Oct;13(10):598-606. doi: 10.1111/ijpo.12394. Epub 2018 Aug 9.

Reference Type BACKGROUND
PMID: 30092608 (View on PubMed)

Gomes RM, Bueno FG, Schamber CR, de Mello JCP, de Oliveira JC, Francisco FA, Moreira VM, Junior MDF, Pedrino GR, de Freitas Mathias PC, Miranda RA, de Moraes SMF, Natali MRM. Maternal diet-induced obesity during suckling period programs offspring obese phenotype and hypothalamic leptin/insulin resistance. J Nutr Biochem. 2018 Nov;61:24-32. doi: 10.1016/j.jnutbio.2018.07.006. Epub 2018 Jul 25.

Reference Type BACKGROUND
PMID: 30179726 (View on PubMed)

Rughani A, Friedman JE, Tryggestad JB. Type 2 Diabetes in Youth: the Role of Early Life Exposures. Curr Diab Rep. 2020 Aug 7;20(9):45. doi: 10.1007/s11892-020-01328-6.

Reference Type BACKGROUND
PMID: 32767148 (View on PubMed)

Suwaydi MA, Zhou X, Perrella SL, Wlodek ME, Lai CT, Gridneva Z, Geddes DT. The Impact of Gestational Diabetes Mellitus on Human Milk Metabolic Hormones: A Systematic Review. Nutrients. 2022 Sep 1;14(17):3620. doi: 10.3390/nu14173620.

Reference Type BACKGROUND
PMID: 36079876 (View on PubMed)

Whitaker KM, Marino RC, Haapala JL, Foster L, Smith KD, Teague AM, Jacobs DR, Fontaine PL, McGovern PM, Schoenfuss TC, Harnack L, Fields DA, Demerath EW. Associations of Maternal Weight Status Before, During, and After Pregnancy with Inflammatory Markers in Breast Milk. Obesity (Silver Spring). 2017 Dec;25(12):2092-2099. doi: 10.1002/oby.22025. Epub 2017 Oct 6.

Reference Type BACKGROUND
PMID: 28985033 (View on PubMed)

Ramos-Roman MA. Breast Milk: A Postnatal Link Between Maternal Life Choices and the Prevention of Childhood Obesity. Clin Ther. 2018 Oct;40(10):1655-1658. doi: 10.1016/j.clinthera.2018.08.018. Epub 2018 Sep 20.

Reference Type BACKGROUND
PMID: 30243769 (View on PubMed)

Peila C, Gazzolo D, Bertino E, Cresi F, Coscia A. Influence of Diabetes during Pregnancy on Human Milk Composition. Nutrients. 2020 Jan 9;12(1):185. doi: 10.3390/nu12010185.

Reference Type BACKGROUND
PMID: 31936574 (View on PubMed)

Fardet A. Minimally processed foods are more satiating and less hyperglycemic than ultra-processed foods: a preliminary study with 98 ready-to-eat foods. Food Funct. 2016 May 18;7(5):2338-46. doi: 10.1039/c6fo00107f. Epub 2016 Apr 29.

Reference Type BACKGROUND
PMID: 27125637 (View on PubMed)

Musa-Veloso K, Noori D, Venditti C, Poon T, Johnson J, Harkness LS, O'Shea M, Chu Y. A Systematic Review and Meta-Analysis of Randomized Controlled Trials on the Effects of Oats and Oat Processing on Postprandial Blood Glucose and Insulin Responses. J Nutr. 2021 Feb 1;151(2):341-351. doi: 10.1093/jn/nxaa349.

Reference Type BACKGROUND
PMID: 33296453 (View on PubMed)

Shkembi B, Huppertz T. Glycemic Responses of Milk and Plant-Based Drinks: Food Matrix Effects. Foods. 2023 Jan 18;12(3):453. doi: 10.3390/foods12030453.

Reference Type BACKGROUND
PMID: 36765982 (View on PubMed)

Shimamura Y, Inagaki R, Oike M, Dong B, Gong W, Masuda S. Glycidol Fatty Acid Ester and 3-Monochloropropane-1,2-Diol Fatty Acid Ester in Commercially Prepared Foods. Foods. 2021 Nov 24;10(12):2905. doi: 10.3390/foods10122905.

Reference Type BACKGROUND
PMID: 34945456 (View on PubMed)

Provided Documents

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Document Type: Informed Consent Form

View Document

Related Links

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https://www.semanticscholar.org/paper/Plant-based-meat-analogues%3A-from-niche-to-Boukid/d5393989aadf2ce9eb97ca79d0a4e9e75bb0eaec

Boukid F. Plant-based meat analogues: from niche to mainstream. Eur Food Res Technol. 2021;247(2):297-308. doi:10.1007/s00217-020-03630-9

Other Identifiers

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00004375

Identifier Type: -

Identifier Source: org_study_id