Abstract
Obesity is a major public health problem and cause of significant burden across the lifespan. Longitudinal samples, beginning in early childhood offer an advantageous approach to studying obesity, given the potential to observe within-individual changes over time. Yet among the many available longitudinal studies of children, particularly those studying psychological disorders, do not assess for overweight/obesity status or related constructs necessary to compute BMI. We offer a unique thin slice approach for assessing obesity/overweight status using previously collected video data. The current study observationally coded overweight/obesity status in a clinically enriched sample of preschoolers oversampled for depression (N = 299). Preschoolers (ages 3–6 years) completed 1–8 structured observational tasks with an experimenter. Overweight/obesity was coded using a “thin slice” technique with 7820 unique ratings available for analysis. Parent-reported physical health problems were assessed throughout the study and BMI percentiles were available from ages 8–19 years. Thin-slice ratings of overweight/obesity were reliably observed in preschoolers’ ages 3–6 years. Thin-slice ratings of overweight/obesity during preschool significantly predicted adolescent BMI percentiles at six separate assessments spanning ages 8–19 years. Further, preschool overweight/obese thin-slice ratings were associated with more physical health problems over time and less sport/activity participation during preschool. Overweight/obesity can be observationally identified in preschool-age children and offers a reliable estimate of future BMI percentile. Study findings highlight how previously collected data could be utilized to study the developmental trajectories of overweight/obesity to inform this critical public health problem.
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Data available on request due to privacy/ethical reasons.
References
Ambady, N., & Rosenthal, R. (1992). Thin slices of expressive behavior as predictors of interpersonal consequences: A meta-analysis. Psychological Bulletin, 111(2), 256–274. https://insights.ovid.com/psychological-bulletin/plbul/1992/03/000/thin-slices-expressive-behavior-predictors/3/00006823.
Bohnert, A. M., Loren, D. M., & Miller, A. L. (2020). Examining childhood obesity through the lens of developmental psychopathology: Framing the issues to guide best practices in research and intervention. American Psychologist, 75(2), 163–177. https://doi.org/10.1037/amp0000581.
Borkenau, P., Mauer, N., Riemann, R., Spinath, F. M., & Angleitner, A. (2004). Thin slices of behavior as cues of personality and intelligence. Journal of Personality and Social Psychology, 86(4), 599–614. https://doi.org/10.1037/0022-3514.86.4.599.
Carney, D. R., Colvin, C. R., & Hall, J. A. (2007). A thin slice perspective on the accuracy of first impressions. Journal of Research in Personality, 41(5), 1054–1072. https://doi.org/10.1016/j.jrp.2007.01.004.
Connelly, B. S., & Ones, D. S. (2010). An other perspective on personality: Meta-analytic integration of observers’ accuracy and predictive validity. Psychological Bulletin, 136(6), 1092–1122.
Davis-Kean, P. E., Jager, J., & Maslowsky, J. (2015). Answering developmental questions using secondary data. Child Development Perspectives, 9(4), 256–261. https://doi.org/10.1111/cdep.12151.
Egger, H. L., Ascher, B., & Angold, A. (2003). The preschool age psychiatric assessment: Version 1.4. Center for Developmental Epidemiology, Department of Psychiatry and Behavioral Sciences. Duke University Medical Center, Durham, NC.
Egger, H. L., Erkanli, A., Keeler, G., Potts, E., Waltr, B. K., & Angold, A. (2006). Test-retest reliability of the preschool age psychiatric assessment (PAPA). Journal of the American Academy of Child & Adolescent Psychiatry, 45(5), 538–549. https://doi.org/10.1097/01.chi.0000205705.71194.b8.
Essex, M. J., Boyce, W. T., Goldstein, L., Armstrong, J., Kraemer, H. C., & Kupfer, D. J. (2002). The confluence of mental, physical, social, and academic difficulties in middle childhood. II: Developing the MacArthur Health and Behavior Questionnaire. Journal of the American Academy of Child & Adolescent Psychiatry, 41(5), 588–603. https://doi.org/10.1097/00004583-200205000-00017.
Feldt, L. S., Woodruff, D. J., & Salih, F. A. (1987). Statistical inference for coefficient alpha. Applied Psychological Measurement, 11(1), 93–103.
Gilbert, K. E., Whalen, D. J., Jackson, J. J., Tillman, R., Barch, D. M., & Luby, J. L. (2020). Thin slice derived personality types predict longitudinal symptom trajectories. Personality Disorders: Theory, Research, Treatment. https://doi.org/10.1037/per0000455
Gilbert, K. E., Whalen, D. J., Tillman, R., Barch, D. M., Luby, J. L., & Jackson, J. J. (2019). Observed personality in preschool: Associations with current and longitudinal symptoms. Journal of Abnormal Child Psychology, 47(12), 1875–1888. https://doi.org/10.1007/s10802-019-00567-w.
Goldsmith, H., Reilly, J., Lemery, K., Longley, S., & Prescott, A. (1999). Laboratory temperament assessment battery: Preschool version (version 1.0, technical report). Department of Psychology, University of Wisconsin, Madison, WI.
Harrison, K., Bost, K. K., McBride, B. A., Donovan, S. M., Grigsby-Toussaint, D. S., Kim, J., Liechty, J. M., Wiley, A., Teran-Garcia, M., & Jacobsohn, G. C. (2011). Toward a developmental conceptualization of contributors to overweight and obesity in childhood: The six-Cs model. Child Development Perspectives, 5(1), 50–58. https://doi.org/10.1111/j.1750-8606.2010.00150.x.
Hayes, A., Chevalier, A., D’Souza, M., Baur, L., Wen, L. M., & Simpson, J. (2016). Early childhood obesity: Association with healthcare expenditure in Australia. Obesity, 24(8), 1752–1758.
Hirschmann, N., Kastner-Koller, U., Deimann, P., Schmelzer, M., & Pietschnig, J. (2018). Reliable and valid coding of thin slices of video footage: Applicability to the assessment of mother-child interactions. Journal of Psychopathology and Behavioral Assessment, 40(2), 249–258. https://doi.org/10.1007/s10862-017-9630-x.
Kaczmarek, L. D., Behnke, M., Kashdan, T. B., Kusiak, A., Marzec, K., Mistrzak, M., & Włodarczyk, M. (2017). Smile intensity in social networking profile photographs is related to greater scientific achievements. The Journal of Positive Psychology, 0(0), 1–5. https://doi.org/10.1080/17439760.2017.1326519.
Koo, T. K., & Li, M. Y. (2016). A guideline of selecting and reporting Intraclass correlation coefficients for reliability research. Journal of Chiropractic Medicine, 15(2), 155–163. https://doi.org/10.1016/j.jcm.2016.02.012.
Kraus, M. W., & Keltner, D. (2009). Signs of socioeconomic status: A thin-slicing approach. Psychological Science, 20(1), 99–106. https://doi.org/10.1111/j.1467-9280.2008.02251.x.
Kraus, M. W., Torrez, B., Park, J. W., & Ghayebi, F. (2019). Evidence for the reproduction of social class in brief speech. Proceedings of the National Academy of Sciences, 116(46), 22998–23003. https://doi.org/10.1073/pnas.1900500116.
Kuczmarski, R. J., Ogden, C. L., Guo, S. S., Grummer-Strawn, L. M., Flegal, K. M., Mei, Z., Wei, R., Curtin, L. R., Roche, A. F., & Johnson, C. L. (2002). 2000 CDC growth charts for the United States: Methods and development. Vital and Health Statistics. Series 11. Data from the National Health Survey, 246, 1–190.
Kumar, S., & Kelly, A. S. (2017). Review of childhood obesity: From epidemiology, etiology, and comorbidities to clinical assessment and treatment. Mayo Clinic Proceedings, 92(2), 251–265. https://doi.org/10.1016/j.mayocp.2016.09.017.
Luby, J. L., Belden, A. C., Pautsch, J., Si, X., & Spitznagel, E. (2009a). The clinical significance of preschool depression: Impairment in functioning and clinical markers of the disorder. Journal of Affective Disorders, 112(1–3), 111–119. https://doi.org/10.1016/j.jad.2008.03.026.
Luby, J. L., Heffelfinger, A., Koenig-McNaught, A. L., Brown, K., & Spitznagel, E. (2004). The preschool feelings checklist: A brief and sensitive screening measure for depression in young children. Journal of the American Academy of Child & Adolescent Psychiatry, 43(6), 708–717. https://doi.org/10.1097/01.chi.0000121066.29744.08.
Luby, J. L., Si, X., Belden, A. C., Tandon, M., & Spitznagel, E. (2009b). Preschool depression: Homotypic continuity and course over 24 months. Archives of General Psychiatry, 66(8), 897–905. https://doi.org/10.1001/archgenpsychiatry.2009.97.
McLoyd, V. C. (1998). Socioeconomic disadvantage and child development. American Psychologist, 53(2), 185–204. https://doi.org/10.1037/0003-066X.53.2.185.
Murphy, N. A., Hall, J. A., Ruben, M. A., Frauendorfer, D., Schmid Mast, M., Johnson, K. E., & Nguyen, L. (2019). Predictive validity of thin-slice nonverbal behavior from social interactions. Personality and Social Psychology Bulletin, 45(7), 983–993. https://doi.org/10.1177/0146167218802834.
Murphy, N. A., Hall, J. A., Schmid Mast, M., Ruben, M. A., Frauendorfer, D., Blanch-Hartigan, D., Roter, D. L., & Nguyen, L. (2015). Reliability and validity of nonverbal thin slices in social interactions. Personality and Social Psychology Bulletin, 41(2), 199–213. https://doi.org/10.1177/0146167214559902.
Nelson, T. F., Stovitz, S. D., Thomas, M., LaVoi, N. M., Bauer, K. W., & Neumark-Sztainer, D. (2011). Do youth sports prevent pediatric obesity? A systematic review and commentary. Current Sports Medicine Reports, 10(6), 360–370. https://doi.org/10.1249/JSR.0b013e318237bf74.
Ogden, C. L., Carroll, M. D., Lawman, H. G., et al. (2016). Trends in obesity prevalence among children and adolescents in the United States, 1988-1994 through 2013-2014. JAMA, 315(21), 2292–2299. https://doi.org/10.1001/jama.2016.6361.
Prime, H., Perlman, M., Tackett, J. L., & Jenkins, J. M. (2014). Cognitive sensitivity in sibling interactions: Development of the construct and comparison of two coding methodologies. Early Education and Development, 25(2), 240–258. https://doi.org/10.1080/10409289.2013.821313.
Pulgarón, E. R. (2013). Childhood obesity: A review of increased risk for physical and psychological comorbidities. Clinical Therapeutics, 35(1), A18–A32. https://doi.org/10.1016/j.clinthera.2012.12.014.
Russell, C. G., & Russell, A. (2019). A biopsychosocial approach to processes and pathways in the development of overweight and obesity in childhood: Insights from developmental theory and research. Obesity Reviews, 20(5), 725–749. https://doi.org/10.1111/obr.12838.
SAS Program ( ages 0 to < 20 years) | Resources | Growth Chart Training | Nutrition | DNPAO | CDC. (2019, February 26). https://www.cdc.gov/nccdphp/dnpao/growthcharts/resources/sas.htm
Simmonds, M., Llewellyn, A., Owen, C. G., & Woolacott, N. (2016). Predicting adult obesity from childhood obesity: A systematic review and meta-analysis. Obesity Reviews, 17(2), 95–107. https://doi.org/10.1111/obr.12334.
Skinner, A. C., & Skelton, J. A. (2014). Prevalence and trends in obesity and severe obesity among children in the United States, 1999-2012. JAMA Pediatrics, 168(6), 561–566. https://doi.org/10.1001/jamapediatrics.2014.21.
Slepian, M. L., Bogart, K. R., & Ambady, N. (2014). Thin-slice judgments in the clinical context. Annual Review of Clinical Psychology, 10(1), 131–153. https://doi.org/10.1146/annurev-clinpsy-090413-123522.
Tackett, J. L., Herzhoff, K., Kushner, S. C., & Rule, N. (2016). Thin slices of child personality: Perceptual, situational, and behavioral contributions. Journal of Personality and Social Psychology, 110(1), 150–166. https://doi.org/10.1037/pspp0000044.
Tackett, J. L., Lang, J. W. B., Markon, K. E., & Herzhoff, K. (2019). A correlated traits, correlated methods model for thin-slice child personality assessment. Psychological Assessment, 31(4), 545–556. https://doi.org/10.1037/pas0000635.
Tackett, J. L., Smack, A. J., Herzhoff, K., Reardon, K. W., Daoud, S., & Granic, I. (2017). Measuring child personality when child personality was not measured: Application of a thin-slice approach. Personality and Mental Health, 11(1), 4–13. https://doi.org/10.1002/pmh.1351.
Uwaezuoke, S. N., Eneh, C. I., & Ndu, I. K. (2017). Relationship between exclusive breastfeeding and lower risk of childhood obesity: A narrative review of published evidence. Clinical Medicine Insights: Pediatrics, 11, 1179556517690196. https://doi.org/10.1177/1179556517690196.
Wang, L., Collins, C., Ratliff, M., Xie, B., & Wang, Y. (2017). Breastfeeding reduces childhood obesity risks. Childhood Obesity, 13(3), 197–204. https://doi.org/10.1089/chi.2016.0210.
Whalen, D. J., Belden, A. C., Tillman, R., Barch, D. M., & Luby, J. L. (2016). Early adversity, Psychopathology, and Latent Class Profiles of Global Physical Health From Preschool Through Early Adolescence. Psychosomatic Medicine, 1, 1008–1018. https://doi.org/10.1097/PSY.0000000000000398.
Whalen, D. J., Gilbert, K. E., Jackson, J. J., Barch, D. M., & Luby, J. L. (2020). Using a thin slice coding approach to assess preschool personality dimensions. Journal of Personality Assessment, 0(0), 1–10. https://doi.org/10.1080/00223891.2020.1722140.
Acknowledgments
The authors wish to thank the children and caregivers of the Preschool Depression Study for their time and dedication to this project. The authors also wish to thank the staff and students of the Early Emotional Development Program for their tireless efforts in the coding of preschool overweight/obesity.
Funding
All phases of this study were supported by an NIH grant, R01 MH064769-06A1 (PI:s Barch and Luby). Dr. Gilbert’s work was supported by K23 MH115074–01 (PI: Gilbert). Dr. Whalen’s work was supported by NIH grants: K23 MH118426–01 (PI: Whalen) and L30 MH108015 (PI: Whalen).
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Highlights
• We offer a unique method for leveraging existing observational data to assess childhood overweight/obesity, the costliest and most impairing public health issue of our time.
• A thin slice coding technique examined whether overweight/obese status can be reliably identified in observations of preschoolers by unacquainted observers.
• Overweight/obesity can be observationally identified in preschool-age children and offers a reliable estimate of future BMI percentile.
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Whalen, D.J., Gilbert, K.E., Barch, D.M. et al. Using a thin slice coding approach to assess preschool overweight and obesity. Curr Psychol 42, 3991–4000 (2023). https://doi.org/10.1007/s12144-021-01761-0
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DOI: https://doi.org/10.1007/s12144-021-01761-0