Fiber-rich Foods, Weight Status, and the Gut Microbiota in NH Hispanic Adults at Risk for Food Insecurity
NCT ID: NCT05488912
Last Updated: 2025-03-28
Study Results
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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COMPLETED
61 participants
OBSERVATIONAL
2022-03-28
2024-10-10
Brief Summary
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Detailed Description
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The study involves biospecimen collection including a pre-collected stool sample, a fasting blood sample, and a Mixed Meal Tolerance Test (MMTT). In addition, participants will answer questionnaires on dietary intake, food insecurity and access, physical activity, eating behavior, and sociodemographic characteristics.
Pre-collected stool samples will be obtained from participants. Anthropometric measurements will be collected at the time of the study visit including height, weight, and waist and hip circumference. BMI will be calculated. An intra-venous catheter will be inserted by a healthcare professional to first collect a fasting blood sample, and will remain inserted for all following blood samples. Subjects will then undergo a Mixed Meal Tolerance Test (MMTT), a validated metabolic assessment in which the participant ingests a liquid mixed meal (e.g., Boost or Ensure), and blood samples are subsequently collected 15min, 30min, 60min and 120min after meal ingestion.
In the intervals between blood sample collections, subjects will complete questionnaires on dietary intake, food insecurity and access, physical activity, eating behavior, and sociodemographic characteristics. The following validated measures will be used to assess these aims:
* USDA Household Food Sufficiency Questionnaire
* Perceived Nutrition Environment Measurements Survey (NEMS-P)
* Shortened version of the Three Factor Eating Questionnaire
* Latino Dietary Behaviors Questionnaire (LDBQ)
* Global Physical Activity Questionnaire
* Short Acculturation Scale for Hispanics
* NHANES Weight History Questionnaire
* Medical History Questionnaire
Conditions
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Study Design
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OTHER
CROSS_SECTIONAL
Study Groups
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Healthy BMI (20-25 kg/m2, n=30)
A group of 30 Hispanic/Latino adults who are NH residents residing in SNAP-eligible households, and have a BMI between 20 and 25 kg/m2.
No interventions assigned to this group
Overweight/Obese BMI (>28 kg/m2, n=30)
A group of 30 Hispanic/Latino adults who are NH residents residing in SNAP-eligible households, and have a BMI greater than or equal to 28 kg/m2.
No interventions assigned to this group
Eligibility Criteria
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Inclusion Criteria
1. Healthy BMI (20-25 kg/m2, n=30), and
2. Overweight/Obese BMI (\>28 kg/m2, n=30)
* Adult men and women (18-55 years of age) residing in a SNAP-eligible households;
* Self-identifying as Hispanic or Latino, and with origin or cultural background from a Spanish-speaking Latin American country;
* Willingness and ability to provide a signed informed consent; and
* Willingness to complete study visits and participate in all aspects of the study.
Exclusion Criteria
* Diagnosed type 2 diabetes, chronic kidney or liver disease, cancer, chronic gastrointestinal conditions, cognitive impairment or incapacitating mental health problems, lack of mobility and physical independence, self-reported weight loss \>5 kg within past 6 months, history of communicable or chronic diseases, medication use or surgery that would preclude safe and active study participation, bariatric surgery, antibiotic use within past 3 months, ongoing participation in other clinical trials, use of anti-obesity medications within the past year, inability to communicate in oral and written form in English and/or Spanish, and habitual consumption of more than two alcoholic drinks per day or of illegal drugs.
18 Years
55 Years
ALL
Yes
Sponsors
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New Hampshire Agricultural Experiment Station
UNKNOWN
University of New Hampshire
OTHER
Responsible Party
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Maria Carlota Dao
Assistant Professor of Human Nutrition
Locations
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University of New Hampshire Health & Wellness
Durham, New Hampshire, United States
Countries
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References
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New Hampshire Department of Health and Human Services. Do I Qualify? NHEasy Gateway to Services https://nheasy.nh.gov/#/screening.
Besser RE, Jones AG, McDonald TJ, Shields BM, Knight BA, Hattersley AT. The impact of insulin administration during the mixed meal tolerance test. Diabet Med. 2012 Oct;29(10):1279-84. doi: 10.1111/j.1464-5491.2012.03649.x.
NCCIH Clinical Research Toolbox. https://www.nccih.nih.gov/grants/toolbox (2020).
2020 Census Questionnaire. https://www.census.gov/programs-surveys/decennial-census/technical-documentation/questionnaires/2020.html (2020).
Jauregui-Lobera I, Garcia-Cruz P, Carbonero-Carreno R, Magallares A, Ruiz-Prieto I. Psychometric properties of Spanish version of the Three-Factor Eating Questionnaire-R18 (Tfeq-Sp) and its relationship with some eating- and body image-related variables. Nutrients. 2014 Dec 4;6(12):5619-35. doi: 10.3390/nu6125619.
Fernandez S, Olendzki B, Rosal MC. A dietary behaviors measure for use with low-income, Spanish-speaking Caribbean Latinos with type 2 diabetes: the Latino Dietary Behaviors Questionnaire. J Am Diet Assoc. 2011 Apr;111(4):589-99. doi: 10.1016/j.jada.2011.01.015.
Arredondo EM, Sotres-Alvarez D, Stoutenberg M, Davis SM, Crespo NC, Carnethon MR, Castaneda SF, Isasi CR, Espinoza RA, Daviglus ML, Perez LG, Evenson KR. Physical Activity Levels in U.S. Latino/Hispanic Adults: Results From the Hispanic Community Health Study/Study of Latinos. Am J Prev Med. 2016 Apr;50(4):500-508. doi: 10.1016/j.amepre.2015.08.029. Epub 2015 Nov 18.
Marin, G., Sabogal, F., Marin, B. V., Otero-Sabogal, R. & Perez-Stable, E. J. Development of a Short Acculturation Scale for Hispanics. Hispanic Journal of Behavioral Sciences 9, 183-205 (1987).
NHANES 2017-2018 Questionnaire Instruments. https://wwwn.cdc.gov/nchs/nhanes/continuousnhanes/questionnaires.aspx?BeginYear=2017.
Svedlund J, Sjodin I, Dotevall G. GSRS--a clinical rating scale for gastrointestinal symptoms in patients with irritable bowel syndrome and peptic ulcer disease. Dig Dis Sci. 1988 Feb;33(2):129-34. doi: 10.1007/BF01535722.
Vandeputte D, Falony G, Vieira-Silva S, Tito RY, Joossens M, Raes J. Stool consistency is strongly associated with gut microbiota richness and composition, enterotypes and bacterial growth rates. Gut. 2016 Jan;65(1):57-62. doi: 10.1136/gutjnl-2015-309618. Epub 2015 Jun 11.
Harrison GG, Stormer A, Herman DR, Winham DM. Development of a spanish-language version of the U.S. household food security survey module. J Nutr. 2003 Apr;133(4):1192-7. doi: 10.1093/jn/133.4.1192.
Green SH, Glanz K. Development of the Perceived Nutrition Environment Measures Survey. Am J Prev Med. 2015 Jul;49(1):50-61. doi: 10.1016/j.amepre.2015.02.004.
New Hampshire Food Access Map. https://unhcoopext.maps.arcgis.com/apps/MapSeries/index.html?appid=5caa235e0e024beb8bebba50a0297d15&entry=2.
Babey, S. H., Diamant, A., Hastert, T. A., Goldstein, H. & Al., E. Designed for Disease: The Link Between Local Food Environments and Obesity and Diabetes. (2008).
Dietary Screener Questionnaire in the NHANES 2009-10: Background. https://epi.grants.cancer.gov/nhanes/dietscreen/.
Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Huntley J, Fierer N, Owens SM, Betley J, Fraser L, Bauer M, Gormley N, Gilbert JA, Smith G, Knight R. Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J. 2012 Aug;6(8):1621-4. doi: 10.1038/ismej.2012.8. Epub 2012 Mar 8.
Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, Alexander H, Alm EJ, Arumugam M, Asnicar F, Bai Y, Bisanz JE, Bittinger K, Brejnrod A, Brislawn CJ, Brown CT, Callahan BJ, Caraballo-Rodriguez AM, Chase J, Cope EK, Da Silva R, Diener C, Dorrestein PC, Douglas GM, Durall DM, Duvallet C, Edwardson CF, Ernst M, Estaki M, Fouquier J, Gauglitz JM, Gibbons SM, Gibson DL, Gonzalez A, Gorlick K, Guo J, Hillmann B, Holmes S, Holste H, Huttenhower C, Huttley GA, Janssen S, Jarmusch AK, Jiang L, Kaehler BD, Kang KB, Keefe CR, Keim P, Kelley ST, Knights D, Koester I, Kosciolek T, Kreps J, Langille MGI, Lee J, Ley R, Liu YX, Loftfield E, Lozupone C, Maher M, Marotz C, Martin BD, McDonald D, McIver LJ, Melnik AV, Metcalf JL, Morgan SC, Morton JT, Naimey AT, Navas-Molina JA, Nothias LF, Orchanian SB, Pearson T, Peoples SL, Petras D, Preuss ML, Pruesse E, Rasmussen LB, Rivers A, Robeson MS 2nd, Rosenthal P, Segata N, Shaffer M, Shiffer A, Sinha R, Song SJ, Spear JR, Swafford AD, Thompson LR, Torres PJ, Trinh P, Tripathi A, Turnbaugh PJ, Ul-Hasan S, van der Hooft JJJ, Vargas F, Vazquez-Baeza Y, Vogtmann E, von Hippel M, Walters W, Wan Y, Wang M, Warren J, Weber KC, Williamson CHD, Willis AD, Xu ZZ, Zaneveld JR, Zhang Y, Zhu Q, Knight R, Caporaso JG. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol. 2019 Aug;37(8):852-857. doi: 10.1038/s41587-019-0209-9. No abstract available.
Callahan BJ, Sankaran K, Fukuyama JA, McMurdie PJ, Holmes SP. Bioconductor Workflow for Microbiome Data Analysis: from raw reads to community analyses. F1000Res. 2016 Jun 24;5:1492. doi: 10.12688/f1000research.8986.2. eCollection 2016.
Varemo L, Nielsen J, Nookaew I. Enriching the gene set analysis of genome-wide data by incorporating directionality of gene expression and combining statistical hypotheses and methods. Nucleic Acids Res. 2013 Apr;41(8):4378-91. doi: 10.1093/nar/gkt111. Epub 2013 Feb 26.
Benjamini, Y. & Hochberg, Y. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society. Series B (Methodological) 57, 289-300 (1995).
Dao MC, Everard A, Aron-Wisnewsky J, Sokolovska N, Prifti E, Verger EO, Kayser BD, Levenez F, Chilloux J, Hoyles L; MICRO-Obes Consortium; Dumas ME, Rizkalla SW, Dore J, Cani PD, Clement K. Akkermansia muciniphila and improved metabolic health during a dietary intervention in obesity: relationship with gut microbiome richness and ecology. Gut. 2016 Mar;65(3):426-36. doi: 10.1136/gutjnl-2014-308778. Epub 2015 Jun 22.
Other Identifiers
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UNH-10-FY2021_49-01
Identifier Type: -
Identifier Source: org_study_id
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