Diet Quality and Visceral Adiposity among a Multiethnic Population of Young, Middle, and Older Aged Adults

Chloe E Panizza, Michael C Wong, Nisa Kelly, Yong En Liu, Yurii B Shvetsov, Dylan A Lowe, Ethan J Weiss, Steven B Heymsfield, Samantha Kennedy, Carol J Boushey, Gertraud Maskarinec, John A Shepherd, Chloe E Panizza, Michael C Wong, Nisa Kelly, Yong En Liu, Yurii B Shvetsov, Dylan A Lowe, Ethan J Weiss, Steven B Heymsfield, Samantha Kennedy, Carol J Boushey, Gertraud Maskarinec, John A Shepherd

Abstract

Background: Visceral adiposity, more so than overall adiposity, is associated with chronic disease and mortality. There has been, to our knowledge, little research exploring the association between diet quality and visceral adipose tissue (VAT) among a mulitethnic population aged 18-80 y.

Objective: The primary objective of this cross-sectional analysis was to examine the association between diet quality [Healthy Eating Index-2010 (HEI-2010) scores] and VAT among a multiethnic population of young, middle, and older aged adults in the United States. Secondary objectives were to repeat these analyses with overall adiposity and blood-based biomarkers for type 2 diabetes and cardiovascular disease risk as outcome measures.

Methods: A total of 540 adults (dropped out: n = 4; age: 18-40 y, n = 220; 40-60 y, n = 183; 60-80 y, n = 133) were recruited across 3 sites (Honolulu County, San Francisco, and Baton Rouge) for the Shape Up! Adults study. Whole-body DXA, anthropometry, fasting blood draw, and questionnaires (food frequency, physical activity, and demographic characteristics) were completed. Linear regression was used to assess the associations between HEI-2010 tertiles and VAT and secondary outcome measures among all participants and age-specific strata, while adjusting for known confounders.

Results: VAT, BMI (kg/m2), body fat percentage, total body fat, trunk fat, insulin, and insulin resistance were inversely related to diet quality (all P values < 0.004). When stratified by age, diet quality was inversely associated with VAT among participants aged 60-80 y (P < 0.006) and VAT/subcutaneous adipose tissue (SAT) among participants aged 40-60 y (P < 0.008).

Conclusions: Higher-quality diet was associated with lower VAT, overall adiposity, and insulin resistance among this multiethnic population of young, middle, and older aged adults with ages ranging from 18 to 80 y. More specifically, adherence to a high-quality diet may minimize VAT accumulation in adults aged 60-80 y and preferentially promote storage of SAT compared with VAT in adults aged 40-60 y.This study was registered at clinicaltrials.gov as NCT03637855.

Keywords: DXA; Diet quality; Healthy Eating Index; middle aged adults; multiethnic; obesity; older adults; visceral adipose tissue; young adults.

Copyright © The Author(s) on behalf of the American Society for Nutrition 2020.

Figures

FIGURE 1
FIGURE 1
Flow diagram for the Shape Up! Adults study (NIH RO1DK109008) as of this publication.

References

    1. Montague CT, O'Rahilly S. The perils of portliness: causes and consequences of visceral adiposity. Diabetes. 2000;49:883–8.
    1. Lee M-J, Wu Y, Fried SK. Adipose tissue heterogeneity: implication of depot differences in adipose tissue for obesity complications. Mol Aspects Med. 2013;34:1–11.
    1. US Department of Health and Human Services. [Internet]. Rockville (MD): Agency for Healthcare Research and Quality; 2013; [updated 2018 August; cited Aug 16, 2019]. Managing overweight and obesity in adults: systematic evidence review from the Obesity Expert Panel, 2013. Available from
    1. Tchernof A, Després J-P. Pathophysiology of human visceral obesity: an update. Physiol Rev. 2013;93:359–404.
    1. Després J-P. Cardiovascular disease under the influence of excess visceral fat. Crit Pathw Cardiol. 2007;6:51–9.
    1. Boyko EJ, Fujimoto WY, Leonetti DL, Newell-Morris L. Visceral adiposity and risk of type 2 diabetes: a prospective study among Japanese Americans. Diabetes Care. 2000;23:465–71.
    1. Needland IJ, Turer AT, Ayers CR, Powell-Wiley TM, Vega GL, Farzaneh-Far R, Grundy SM, Khera A, McGuire DK, de Lemos JA. Dysfunctional adiposity and the risk of prediabetes and type 2 diabetes in obese adults. JAMA. 2012;308:1150–9.
    1. Schapira DV, Clark RA, Wolff PA, Jarrett AR, Kumar NB, Aziz NM. Visceral obesity and breast cancer risk. Cancer. 1994;74:632–9.
    1. von Hafe P, Pina F, Pérez A, Tavares M, Barros H. Visceral fat accumulation as a risk factor for prostate cancer. Obes Res. 2004;12:1930–5.
    1. Oh TH, Byeon JS, Myung SJ, Yang SK, Choi KS, Chung JW, Kim B, Lee D, Byun JH, Jang SJet al. . Visceral obesity as a risk factor for colorectal neoplasm. J Gastroenterol Hepatol. 2008;23:411–7.
    1. Kuk JL, Katzmarzyk PT, Nichaman MZ, Church TS, Blair SN, Ross R. Visceral fat is an independent predictor of all-cause mortality in men. Obesity. 2006;14:336–41.
    1. Tsujinaka S, Konishi F, Kawamura YJ, Saito M, Tajima N, Tanaka O, Lefor AT. Visceral obesity predicts surgical outcomes after laparoscopic colectomy for sigmoid colon cancer. Diseases of the Colon & Rectum. 2008;51:1757–65.
    1. Lee SW, Son JY, Kim JM, Hwang SS, Han JS, Heo NJ. Body fat distribution is more predictive of all-cause mortality than overall adiposity. Diabetes Obes Metab. 2018;20:141–7.
    1. Kuk JL, Saunders TJ, Davidson LE, Ross R. Age-related changes in total and regional fat distribution. Ageing Res Rev. 2009;8:339–48.
    1. Ross R, Janiszewski PM. Is weight loss the optimal target for obesity-related cardiovascular disease risk reduction?. Can J Cardiol. 2008;24:25D–31D.
    1. Dorn JM, Hovey K, Muti P, Freudenheim JL, Russell M, Nochajski TH, Trevisan M. Alcohol drinking patterns differentially affect central adiposity as measured by abdominal height in women and men. J Nutr. 2003;133:2655–62.
    1. Fischer K, Pick JA, Moewes D, Nöthlings U. Qualitative aspects of diet affecting visceral and subcutaneous abdominal adipose tissue: a systematic review of observational and controlled intervention studies. Nutr Rev. 2015;73:191–215.
    1. Maskarinec G, Lim U, Jacobs S, Monroe KR, Ernst T, Buchthal SD, Shepherd JA, Wilkens LR, Le Marchand L, Boushey CJ. Diet quality in midadulthood predicts visceral adiposity and liver fatness in older ages: the Multiethnic Cohort study. Obesity. 2017;25:1442–50.
    1. Panizza CE, Lim U, Yonemori KM, Cassel KD, Wilkens LR, Harvie MN, Maskarinec G, Delp EJ, Lampe JW, Shepherd JAet al. . Effects of intermittent energy restriction combined with a Mediterranean diet on reducing visceral adiposity: a randomized active comparator pilot study. Nutrients. 2019;11;1386.
    1. Carroll JF, Chiapa AL, Rodriquez M, Phelps DR, Cardarelli KM, Vishwanatha JK, Bae S, Cardarelli R. Visceral fat, waist circumference, and BMI: impact of race/ethnicity. Obesity. 2008;16:600–7.
    1. Lim U, Monroe KR, Buchthal S, Fan B, Cheng I, Kristal BS, Lampe JW, Hullar MA, Franke AA, Stram DOet al. . Propensity for intra-abdominal and hepatic adiposity varies among ethnic groups. Gastroenterology. 2019;156:966–75.
    1. van Eekelen E, Geelen A, Alssema M, Lamb HJ, de Roos A, Rosendaal FR, de Mutsert R. Adherence to dietary guidelines in relation to visceral fat and liver fat in middle-aged men and women: the NEO study. Int J Obes (Lond). 2019;44:297–306.
    1. Molenaar EA, Massaro JM, Jacques PF, Pou KM, Ellison RC, Hoffmann U, Pencina K, Shadwick SD, Vasan RS, O'Donnell CJet al. . Association of lifestyle factors with abdominal subcutaneous and visceral adiposity: the Framingham Heart Study. Diabetes Care. 2009;32:505–10.
    1. Hu FB. Dietary pattern analysis: a new direction in nutritional epidemiology. Curr Opin Lipidol. 2002;13:3–9.
    1. Setia MS. Methodology series module 5: sampling strategies. Indian J Dermatol. 2016;61:505–9.
    1. Ng BK, Hinton BJ, Fan B, Kanaya AM, Shepherd JA. Clinical anthropometrics and body composition from 3D whole-body surface scans. Eur J Clin Nutr. 2016;70:1265–70.
    1. National Cancer Institute, Epidemiology and Genomics Research Program. [Internet]. [place unknown], Background on Diet History Questionnaire II (DHQ-II) for U.S. & Canada, 2019. [updated April 22, 2019; cited Aug 18, 2019]. Available from: .
    1. Subar AF, Thompson FE, Kipnis V, Midthune D, Hurwitz P, McNutt S, McIntosh A, Rosenfeld S. Comparative validation of the Block, Willett, and National Cancer Institute food frequency questionnaires. Am J Epidemiol. 2001;154:1089–99.
    1. Dixon LB, Zimmerman TP, Kahle LL, Subar AF. Adding carotenoids to the NCI Diet History Questionnaire Database. J Food Compos Anal. 2003;16:269–80.
    1. Subar AF, Midthune D, Kulldorff M, Brown CC, Thompson FE, Kipnis V, Schatzkin A. Evaluation of alternative approaches to assign nutrient values to food groups in food frequency questionnaires. Am J Epidemiol. 2000;152:279–86.
    1. National Cancer Institute, Epidemiology and Genomics Research Program, [Internet]. Development of the DHQ II and C-DHQ II nutrient and food group database, [updated April 25, 2018; cited Aug 20, 2019]. Available from:
    1. National Cancer Institute, Epidemiology and Genomics Research Program, [Internet].Diet History Questionnaire II: calculating Healthy Eating Index (HEI) scores using Diet*Calc output, [updated April 22, 2019; cited Aug 18, 2019]. Available from: .
    1. Guenther PM, Casavale KO, Reedy J, Kirkpatrick SI, Hiza HA, Kuczynski KJ, Kahle LL, Krebs-Smith SM. Update of the Healthy Eating Index: HEI-2010. J Acad Nutr Diet. 2013;113:569–80.
    1. National Cancer Institute, Epidemiology and Genomics Research Program, [Internet]. Overview and Background of the Healthy Eating Index, [updated Aug 13, 2018; cited Aug 18, 2019]. Available from:: .
    1. Amireault S, Godin G. The Godin-Shephard leisure-time physical activity questionnaire: validity evidence supporting its use for classifying healthy adults into active and insufficiently active categories. Percept Mot Skills. 2015;120:604–22.
    1. Centers for Disease Control and Prevention [Internet]. National Health and Nutrition Examination Survey (NHANES): Anthropometry Procedures Manual; 2007. [updated Oct 30, 2018; cited Aug 18, 2019]. Available from:.
    1. Martin CB, Hales CM, Gu Q, Ogden CL. Prescription drug use in the United States, 2015–2016. NCHS Data Brief, no 334 [Internet]. Hyattsville, MD: National Center for Health Statistics; 2019; [updated May 19, 2019; cited April 6, 2020]. Available from.
    1. Dietary Guidelines Advisory Committee. [Internet]. Washington, DC: Scientific report of the 2015 Dietary Guidelines Advisory Committee: Advisory Report to the Secretary of Health and Human Services and the Secretary of Agriculture; 2015. [updated 2020 Jan 30; cited 2019 Aug 15]. Available from.
    1. Harmon BE, Boushey CJ, Shvetsov YB, Ettienne R, Reedy J, Wilkens LR, Le Marchand L, Henderson BE, Kolonel LN. Associations of key diet-quality indexes with mortality in the Multiethnic Cohort: the Dietary Patterns Methods Project. Am J Clin Nutr. 2015;101:587–97.
    1. Stram DO, Hankin JH, Wilkens LR, Pike MC, Monroe KR, Park S, Henderson BE, Nomura AM, Earle ME, Nagamine FSet al. . Calibration of the dietary questionnaire for a multiethnic cohort in Hawaii and Los Angeles. Am J Epidemiol. 2000;151:358–70.
    1. Kipnis V, Subar AF, Midthiune D, Freedman LS, Ballard-Barbash R, Troiano RP, Bingham S, Schoeller DA, Schatzkin A, Carroll RJ. Structure of dietary measurement error: results of the OPEN biomarker study. Am J Epidemiol. 2003;158:14–21.
    1. Subar AF, Thompson FE, Kipnis V, Midthune D, Hurwitz P, McNutt S, McIntosh A, Rosenfeld S. Comparative validation of the Block, Willett, and National Cancer Institute food frequency questionnaires: the Eating at America's Table Study (EATS). Am J Epedemiol. 2001;154:1089–99.
    1. Thompson FE, Subar AF, Brown CC, Smith AF, Sharbaugh CO, Jobe JB, Mittl B, Gibson JT, Ziegler RG. Cognitive research enhances accuracy of food frequency questionnaire reports: results of an experimental validation study. J Am Diet Assoc. 2002;102:212–25.
    1. Seidell JC, Bakker CJ,van der Kooy K. Imaging techniques for measuring adipose-tissue distribution: a comparison between computed tomography and 1.5-T magnetic resonance. Am J Clin Nutr. 1990;51:953–7.
    1. Shuster A, Patlas M, Pinthus JH, Mourtzakis M. The clinical importance of visceral adiposity: a critical review of methods for visceral adipose tissue analysis. Br J Radiol. 2012;85:1–10.
    1. Micklesfield LK, Goedecke JH, Punyanitya M, Wilson KE, Kelly TL. Dual-energy X-ray performs as well as clinical computed tomography for the measurement of visceral fat. Obesity. 2012;20:1109–14.
    1. Kaul S, Rothney MP, Peters DM, Wacker WK, Davis CE, Shapiro MD, Ergun DL. Dual-energy X-Ray absorptiometry for quantification of visceral fat. Obesity. 2012;20:1313–8.
    1. Liese AD, Krebs-Smith SM, Subar AF, George SM, Harmon BE, Neuhouser ML, Boushey CJ, Schap TE, Reedy J. The Dietary Patterns Methods Project: synthesis of findings across cohorts and relevance to dietary guidance. J Nutr. 2015;145:393–402.
    1. Subar AF, Kipnis V, Troiano RP, Midthune D, Schoeller DA, Bingham S, Sharbaugh CO, Trabulsi J, Runswick S, Ballard-Barbash Ret al. . Using intake biomarkers to evaluate the extent of dietary misreporting in a large sample of adults: the OPEN Study. Am J Epidemiol. 2003;158:1–13.

Source: PubMed

Sponsors en medewerkers

Medische omstandigheden

Geneesmiddelinterventies

3
Abonneren