Skin Carotenoid Scores Assessed with Reflection Spectroscopy Are Associated with Self-Reported Fruit and Vegetable Intake Among Latino Early Adolescents

Published:April 02, 2021DOI:



      Latino early adolescents have a high prevalence of overweight and obesity. Interventions to address healthy eating among Latino youth frequently focus on fruit and vegetable (FV) intake. Reflection spectroscopy assessed skin carotenoid (SC) levels has been proposed as an easy, noninvasive method to evaluate FV intake, but validation studies involving ethnically diverse youth are lacking.


      This study aimed to assess the association between reflection spectroscopy-measured SC scores and self-reported FV intake among low-income, urban, Latino early adolescents, controlling for potential confounding factors.


      This study was a cross-sectional secondary analysis of baseline data from a community-based intervention program (Padres Preparados, Jóvenes Saludables) involving Latino fathers and adolescents to improve paternal parenting practices and youth energy balance-related behaviors.


      Participants were 195 low-income, Latino early adolescents (aged 10 to 14 years). Data were collected in the Minneapolis/St Paul metropolitan area from 2017 to 2020 during fall or winter months.

      Main outcome measures

      SC scores were measured using reflection spectroscopy, usual intakes of FV and carotenoid compounds were estimated based on the assessment using 24-hour dietary recalls.

      Statistical analysis

      Multivariable linear regression analyses were used to estimate associations of SC scores and each dietary component and potential confounding factors after assessing variables for inclusion in the analyses.


      The mean SC score was 225 ± 95. The mean FV and total carotenoid intakes were 3.3 ± 0.5 servings/day and 8,360 ± 786 μg/day, respectively. Higher SC scores were observed among youth who had higher FV (β = .37 and P < 0.01) or total carotenoid intakes (β = .31 and P < 0.01). SC scores measured during fall were higher than scores measured during winter. Study participants with higher home FV availability and accessibility had higher SC scores.


      Findings supported using SC score as a potential easy-to-use indicator of FV intake among Latino youth with consideration of seasonal variation and home FV availability and accessibility.


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        • Kim S.A.
        • Moore L.V.
        • Galuska D.
        • et al.
        Vital signs: fruit and vegetable intake among children–United States, 2003–2010.
        Morb Mortal Wkly Rep. 2014; 63: 671-676
        • Moore L.V.
        • Thompson F.E.
        • Demissie Z.
        Percentage of youth meeting federal fruit and vegetable intake recommendations, Youth Risk Behavior Surveillance System, United States and 33 states, 2013.
        J Acad Nutr Diet. 2017; 117: 545-553
      1. 2015-2020 Dietary Guidelines for Americans. 8th edition.
      2. What We Eat in America, DHHS-USDA dietary survey.
        Date accessed: November 20, 2020
        • Xu F.
        • Cohen S.A.
        • Greaney M.L.
        • Hatfield D.L.
        • Greene G.W.
        Racial/ethnic disparities in US adolescents’ dietary quality and its modification by weight-related factors and physical activity.
        Int J Environ Res Public Health. 2019; 16: 4803
        • Dave J.M.
        • Evans A.E.
        • Saunders R.P.
        • Watkins K.W.
        • Pfeiffer K.A.
        Associations among food insecurity, acculturation, demographic factors, and fruit and vegetable intake at home in Hispanic children.
        J Am Diet Assoc. 2009; 109: 697-701
        • Ogden C.L.
        • Fryar C.D.
        • Martin C.B.
        • et al.
        Trends in obesity prevalence by race and Hispanic origin—1999-2000 to 2017-2018.
        JAMA. 2020; 324: 1208-1210
        • Holub C.K.
        • Lobelo F.
        • Mehta S.M.
        • Sanchez R.L.M.
        • Arredondo E.M.
        • Elder J.P.
        School-wide programs aimed at obesity among Latino youth in the United States: a review of the evidence.
        J School Health. 2014; 84: 239-246
        • Kiraly C.
        • Turk M.T.
        • Kalarchian M.A.
        • Shaffer C.
        Applying ecological frameworks in obesity intervention studies in Hispanic/Latino youth: a systematic review.
        Hisp Health Care Int. 2017; 15: 130-142
        • Burrows T.L.
        • Williams R.
        • Rollo M.
        • et al.
        Plasma carotenoid levels as biomarkers of dietary carotenoid consumption: a systematic review of the validation studies.
        J Nutr Intermed Metab. 2015; 2: 15-64
        • Scherr R.E.
        • Laugero K.D.
        • Graham D.J.
        • et al.
        Innovative techniques for evaluating behavioral nutrition interventions.
        Adv Nutr. 2017; 8: 113-125
        • Ermakov I.V.
        • Gellermann W.
        Optical detection methods for carotenoids in human skin.
        Arch Biochem Biophys. 2015; 572: 101-111
        • Radtke M.D.
        • Jilcott Pitts S.
        • Jahns L.
        • et al.
        Criterion-related validity of spectroscopy-based skin carotenoid measurements as a proxy for fruit and vegetable intake: a systematic review.
        Adv Nutr. 2020; 11: 1282-1299
        • Ermakov I.V.
        • Gellermann W.
        Dermal carotenoid measurements via pressure mediated reflection spectroscopy.
        J Biophotonics. 2012; 5: 559-570
        • Mayne S.T.
        • Cartmel B.
        • Scarmo S.
        • Jahns L.
        • Ermakov I.V.
        • Gellerman W.
        Resonance Raman Spectroscopic evaluation of skin carotenoids as a biomarker of carotenoid status for human studies.
        Arch Biochem Biophys. 2013; 539: 163-170
        • Jilcott Pitts S.B.
        • Jahns L.
        • Wu Q.
        • et al.
        A non-invasive assessment of skin carotenoid status through reflection spectroscopy is a feasible, reliable and potentially valid measure of fruit and vegetable consumption in a diverse community sample.
        Public Health Nutr. 2018; 21: 1664-1670
        • Jilcott Pitts S.B.
        • Wu Q.
        • Truesdale K.P.
        • et al.
        One-year follow-up examination of the impact of the North Carolina Healthy Food Small Retailer Program on healthy food availability, purchases, and consumption.
        Int J Environ Res Public Health. 2018; 15: 2681
        • Thomson J.L.
        • Goodman M.H.
        • Landry A.S.
        • Donoghue A.
        • Chandler A.
        • Bilderback R.
        Feasibility of online nutrition education in the workplace: working toward healthy lifestyles.
        J Nutr Educ Behav. 2018; 50: 868-875
        • Bakırcı-Taylor A.L.
        • Reed D.B.
        • McCool B.
        • Dawson J.A.
        mHealth improved fruit and vegetable accessibility and intake in young children.
        J Nutr Educ Behav. 2019; 51: 556-566
        • Rush E.
        • Amoah I.
        • Diep T.
        • Jalili-Moghaddam S.
        Determinants and suitability of carotenoid reflection score as a measure of carotenoid status.
        Nutrients. 2020; 12: 113
        • Jahns L.
        • Johnson L.K.
        • Conrad Z.
        • et al.
        Concurrent validity of skin carotenoid status as a concentration biomarker of vegetable and fruit intake compared to multiple 24-h recalls and plasma carotenoid concentrations across one year: a cohort study.
        Nutr J. 2019; 18: 78
        • Moran N.E.
        • Mohn E.S.
        • Hason N.
        • Erdman Jr., J.W.
        • Johnson E.J.
        Intrinsic and extrinsic factors impacting absorption, metabolism, and health effects of dietary carotenoids.
        Adv Nutr. 2018; 9: 465-492
        • Scarmo S.
        • Henebery K.
        • Peracchio H.
        • et al.
        Skin carotenoid status measured by resonance Raman spectroscopy as a biomarker of fruit and vegetable intake in preschool children.
        Eur J Clin Nutr. 2012; 66: 555-560
        • Scarmo S.
        • Cartmel B.
        • Lin H.
        • et al.
        Single v. multiple measures of skin carotenoids by resonance Raman spectroscopy as a biomarker of usual carotenoid status.
        Br J Nutr. 2013; 110: 911-917
        • Aguilar S.S.
        • Wengreen H.J.
        • Dew J.
        Skin carotenoid response to a high-carotenoid juice in children: a randomized clinical trial.
        J Acad Nutr Diet. 2015; 115: 1771-1778
        • Morgan E.H.
        • Graham M.L.
        • Marshall G.A.
        • Hanson K.L.
        • Seguin-Fowler R.A.
        Serum carotenoids are strongly associated with dermal carotenoids but not self-reported fruit and vegetable intake among overweight and obese women.
        Int J Behav Nutr Phys Act. 2019; 16: 104
        • Zhang Y.
        • Peralta A.R.
        • Brazys P.A.R.
        • Hurtado G.A.
        • Larson N.
        • Reicks M.
        Development of a survey to assess Latino fathers’ parenting practices regarding energy balance-related behaviors of early adolescents.
        Health Educ Behav. 2020; 47: 123-133
        • Ermakov I.V.
        • Ermakova M.
        • Sharifzadeh M.
        • et al.
        Optical assessment of skin carotenoid status as a biomarker of vegetable and fruit intake.
        Arch Biochem Biophys. 2018; 646: 46-54
      3. Nutrition Data System for Research [computer program]. Version 2016. Nutrition Coordinating Center, University of Minnesota, Minneapolis, MN2016
      4. MIXTRAN and INDIVNT Macro [computer program]. Version 2.1, SAS code. Washington, DC: National Cancer Institute; 2012.

        • The Centers for Disease Control and Prevention
        National Health Nutrition Examination Survey Anthropometry Procedures Manual.
        • Kuczmarski R.J.
        • Ogden C.L.
        • Guo S.S.
        • et al.
        2000 CDC growth charts for the United States: methods and development.
        Vital Health Stat. 2002; 11: 1-190
        • Kandula N.R.
        • Diez-Roux A.V.
        • Chan C.
        • et al.
        Association of acculturation levels and prevalence of diabetes in the multiethnic study of atherosclerosis (MESA).
        Diabetes Care. 2008; 31: 1621-1628
        • Hager E.R.
        • Quigg A.M.
        • Black M.M.
        • et al.
        Development and validity of a 2-item screen to identify families at risk for food insecurity.
        Pediatrics. 2010; 126: e26-e32
        • Robinson-O’Brien R.
        • Neumark-Sztainer D.
        • Hannan P.J.
        • Burgess-Champoux T.
        • Haines J.
        Fruits and vegetables at home: child and parent perceptions.
        J Nutr Educ Behav. 2009; 41: 360-364
      5. US Dept of Agriculture, Food and Nutrition Service. Supplemental Nutrition Assistance Program Education (SNAP-Ed).
        Date accessed: November 6, 2020
      6. US Dept of Agriculture, National Institute of Food and Agriculture. Expanded Food and Nutrition Education Program (EFNEP).
        • US Dept of Agriculture, National Institute of Food and Agriculture
        Special Supplemental Nutrition Program for Women, Infants, and Children (WIC).
        Date accessed: November 6, 2020
        • Cooking Matters
        Share our strength.
        Date accessed: November 6, 2020
        • Cohen J.
        Statistical Power Analysis.
        2nd edition. Erlbaum, Hillsdale NJ1988
        • Menard S.
        An introduction to logistic regression diagnostics.
        Applied Logistic Regression Analysis. SAGE Publications, Thousand Oaks, CA2002
      7. IBM SPSS Statistics for Windows [computer program]. Version 26.0. IBM Corporation, Armonk, NY2019
      8. SAS [computer program]. Version 9.4. SAS Institute Inc, Cary, NC2014
        • May K.
        • Jilcott Pitts S.
        • Stage V.C.
        • et al.
        Use of the Veggie Meter as a tool to objectively approximate fruit and vegetable intake among youth for evaluation of preschool and school-based interventions.
        J Hum Nutr Diet. 2020; 33: 869-875
        • Beccarelli L.M.
        • Scherr R.E.
        • Dharmar M.
        • et al.
        Using skin carotenoids to assess dietary changes in students after 1 academic year of participating in the Shaping Healthy Choices Program.
        J Nutr Educ Behav. 2017; 49: 73-78
        • de Gruijl F.R.
        UV adaptation: pigmentation and protection against overexposure.
        Exp Dermatol. 2017; 26: 557-562
        • Neumark-Sztainer D.
        • Wall M.
        • Perry C.
        • Story M.
        Correlates of fruit and vegetable intake among adolescents. Findings from Project EAT.
        Prev Med. 2003; 37: 198-208
        • Willett W.
        Nutritional Epidemiology.
        3rd edition. Oxford University Press, New York, NY2013


      S. Nagao-Sato is a research fellow, Department of Food Science and Nutrition, University of Minnesota, St Paul.


      A. Baltaci is a graduate research assistant, Department of Food Science and Nutrition, University of Minnesota, St Paul.


      A. O. Peralta Reyes is a research coordinator, Extension Center for Family Development, University of Minnesota, St Paul.


      Y. Zhang is a lecturer and research scholar, Department of Child and Adolescent Health and Social Medicine, School of Public Health, Medical College of Soochow University, Suzhou, Jiangsu, China.


      G. A. Hurtado Choque is an assistant professor and extension specialist, School of Public Health, University of Maryland, College Park.


      M. Reicks is a professor and extension nutritionist, Department of Food Science and Nutrition, University of Minnesota, St Paul.