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Clinical relevance and validity of tools to predict infant, childhood and adulthood obesity: a systematic review

  • Oliver J Canfell (a1) (a2), Robyn Littlewood (a1) (a2) (a3), Olivia RL Wright (a1) and Jacqueline L Walker (a1)



To determine the global availability of a multicomponent tool predicting overweight/obesity in infancy, childhood, adolescence or adulthood; and to compare their predictive validity and clinical relevance.


The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed. The databases PubMed, EMBASE, CINAHL, Web of Science and PsycINFO were searched. Additional articles were identified via reference lists of included articles. Risk of bias was assessed using the Academy of Nutrition and Dietetics’ Quality Criteria Checklist. The National Health and Medical Research Council’s Levels of Evidence hierarchy was used to assess quality of evidence. Predictive performance was evaluated using the ABCD framework.


Eligible studies: tool could be administered at any life stage; quantified the risk of overweight/obesity onset; used more than one predictor variable; and reported appropriate prediction statistical outcomes.


Of the initial 4490 articles identified, twelve articles (describing twelve tools) were included. Most tools aimed to predict overweight and/or obesity within childhood (age 2–12 years). Predictive accuracy of tools was consistently adequate; however, the predictive validity of most tools was questioned secondary to poor methodology and statistical reporting. Globally, five tools were developed for dissemination into clinical practice, but no tools were tested within a clinical setting.


To our knowledge, a clinically relevant and highly predictive overweight/obesity prediction tool is yet to be developed. Clinicians can, however, act now to identify the strongest predictors of future overweight/obesity. Further research is necessary to optimise the predictive strength and clinical applicability of such a tool.


Corresponding author

*Corresponding author: Email


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1. World Health Organization (2015) Global Status Report on Noncommunicable Diseases 2014. Geneva: WHO.
2. Dobbs, R, Sawers, C, Thompson, F et al. (2014) Overcoming Obesity: An Initial Economic Analysis. New York: McKinsey Global Institute.
3. Australian Bureau of Statistics (2017) National Health Survey: First Results, 201415 . Canberra, ACT: ABS; available at
4. Klein, JD, Sesselberg, TS, Johnson, MS et al. (2010) Adoption of body mass index guidelines for screening and counseling in pediatric practice. Pediatrics 125, 20082985.
5. Grossman, DC, Bibbins-Domingo, K, Curry, SJ et al. (2017) Screening for obesity in children and adolescents: US Preventive Services Task Force recommendation statement. JAMA 317, 24172426.
6. National Health and Medical Research Council (2013) Clinical Practice Guidelines for the Management of Overweight and Obesity in Adults, Adolescents and Children in Australia. Melbourne, VIC: NHMRC.
7. Hassink, SG (2017) Mobilizing during infancy to prevent severe obesity. J Pediatr 183, 67.
8. Barlow, SE, Bobra, SR, Elliott, MB et al. (2007) Recognition of childhood overweight during health supervision visits: does BMI help pediatricians? Obesity (Silver Spring) 15, 225232.
9. Simmonds, M, Burch, J, Llewellyn, A et al. (2015) The use of measures of obesity in childhood for predicting obesity and the development of obesity-related diseases in adulthood: a systematic review and meta-analysis. Health Technol Assess issue 43, 1336.
10. Zalbahar, N, Najman, J, McIntyre, H et al. (2017) Parental pre‐pregnancy obesity and the risk of offspring weight and body mass index change from childhood to adulthood. Clin Obes 7, 206215.
11. Rath, S, Marsh, J, Newnham, J et al. (2016) Parental pre‐pregnancy BMI is a dominant early‐life risk factor influencing BMI of offspring in adulthood. Obes Sci Pract 2, 4857.
12. Hales, C & Barker, D (2001) The thrifty phenotype hypothesis. Br Med Bull 60, 520.
13. Yu, Z, Han, S, Zhu, G et al. (2011) Birth weight and subsequent risk of obesity: a systematic review and meta‐analysis. Obes Rev 12, 525542.
14. Evensen, E, Emaus, N, Kokkvoll, A et al. (2017) The relation between birthweight, childhood body mass index, and overweight and obesity in late adolescence: a longitudinal cohort study from Norway, The Tromsø Study, Fit Futures. BMJ Open 7, e015576.
15. Ong, KK & Loos, RJ (2006) Rapid infancy weight gain and subsequent obesity: systematic reviews and hopeful suggestions. Acta Paediatr 95, 904908.
16. Ino, T (2010) Maternal smoking during pregnancy and offspring obesity: meta‐analysis. Pediatr Int 52, 9499.
17. Horta, BL, Loret de Mola, C & Victora, CG (2015) Long‐term consequences of breastfeeding on cholesterol, obesity, systolic blood pressure and type 2 diabetes: a systematic review and meta‐analysis. Acta Paediatr 104, 3037.
18. Scott, JA, Ng, SY & Cobiac, L (2012) The relationship between breastfeeding and weight status in a national sample of Australian children and adolescents. BMC Public Health 12, 107.
19. Birbilis, M, Moschonis, G, Mougios, V et al. (2012) Obesity in adolescence is associated with perinatal risk factors, parental BMI and sociodemographic characteristics. Eur J Clin Nutr 67, 115121.
20. Parrino, C, Vinciguerra, F, La Spina, N et al. (2016) Influence of early-life and parental factors on childhood overweight and obesity. J Endocrinol Invest 39, 13151321.
21. Aslam, S & Emmanuel, P (2010) Formulating a researchable question: a critical step for facilitating good clinical research. Indian J Sex Transm Dis 31, 4750.
22. Moher, D, Liberati, A, Tetzlaff, J et al. (2009) Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med 6, e1000097.
23. Eusebi, P (2013) Diagnostic accuracy measures. Cerebrovasc Dis 36, 267272.
24. Steyerberg, EW & Vergouwe, Y (2014) Towards better clinical prediction models: seven steps for development and an ABCD for validation. Eur Heart J 35, 19251931.
25. Lee, Y-H, Bang, H & Kim, DJ (2016) How to establish clinical prediction models. Endocrinol Metab (Seoul) 31, 3844.
26. Dent, THS, Wright, CF, Stephan, BCM et al. (2012) Risk prediction models: a framework for assessment. Public Health Genomics 15, 98105.
27. Academy of Nutrition and Dietetics (2016) Evidence Analysis Manual: Steps in the Academy Evidence Analysis Process. Chicago, IL: Academy of Nutrition and Dietetics.
28. National Health and Medical Research Council (2009) NHMRC Additional Levels of Evidence and Grades for Recommendation for Developers of Guidelines. Canberra, ACT: NHMRC.
29. Timpka, T, Angbratt, M, Bolme, P et al. (2007) A high-precision protocol for identification of preschool children at risk for persisting obesity. PLoS One 2, e535.
30. Classen, T & Hokayem, C (2005) Childhood influences on youth obesity. Econ Hum Biol 3, 165187.
31. de Kroon, ML, Renders, CM, van Wouwe, JP et al. (2011) Identifying young children without overweight at high risk for adult overweight: the Terneuzen Birth Cohort. Int J Pediatr Obes 6, e187e195.
32. Manios, Y, Birbilis, M, Moschonis, G et al. (2013) Childhood Obesity Risk Evaluation based on perinatal factors and family sociodemographic characteristics: CORE index. Eur J Pediatr 172, 551555.
33. Morandi, A, Meyre, D, Lobbens, S et al. (2012) Estimation of newborn risk for child or adolescent obesity: lessons from longitudinal birth cohorts. PLoS One 7, e49919.
34. Pei, Z, Flexeder, C, Fuertes, E et al. (2013) Early life risk factors of being overweight at 10 years of age: results of the German birth cohorts GINIplus and LISAplus. Eur J Clin Nutr 67, 855862.
35. Potter, CM & Ulijaszek, SJ (2013) Predicting adult obesity from measures in earlier life. J Epidemiol Community Health 67, 10321037.
36. Santorelli, G, Petherick, ES, Wright, J et al. (2013) Developing prediction equations and a mobile phone application to identify infants at risk of obesity. PLoS One 8, e71183.
37. Steur, M, Smit, HA, Schipper, CM et al. (2011) Predicting the risk of newborn children to become overweight later in childhood: the PIAMA birth cohort study. Int J Pediatr Obes 6, e170e178.
38. Weng, SF, Redsell, SA, Nathan, D et al. (2013) Estimating overweight risk in childhood from predictors during infancy. Pediatrics 132, e414e421.
39. Seyednasrollah, F, Makela, J, Pitkanen, N et al. (2017) Prediction of adulthood obesity using genetic and childhood clinical risk factors in the Cardiovascular Risk in Young Finns study. Circ Cardiovasc Genet 10, e001554.
40. Druet, C, Stettler, N, Sharp, S et al. (2012) Prediction of childhood obesity by infancy weight gain: an individual-level meta-analysis. Paediatr Perinat Epidemiol 26, 1926.
41. Hosmer, DW, Lemeshow, S & Sturdivant, RX (2013) Applied Logistic Regression, 3rd ed. Hoboken, NJ: Wiley.
42. Bouwmeester, W, Zuithoff, NPA, Mallett, S et al. (2012) Reporting and methods in clinical prediction research: a systematic review. PLoS Med 9, e1001221.
43. Mallett, S, Halligan, S, Thompson, M et al. (2012) Interpreting diagnostic accuracy studies for patient care. BMJ 345, e3999.
44. Campbell, M, Bryson, H & Wake, M (2010) The burden of childhood obesity in Australian paediatric practice: children attending paediatricians survey. J Paediatr Child Health 46, 12.
45. Juonala, M, Juhola, J, Magnussen, CG et al. (2011) Childhood environmental and genetic predictors of adulthood obesity: the Cardiovascular Risk in Young Finns study. J Clin Endocrinol Metab 96, E1542E1549.
46. Damschroder, LJ, Aron, DC, Keith, RE et al. (2009) Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implement Sci 4, 50.
47. Guo, SS, Huang, C, Maynard, LM et al. (2000) Body mass index during childhood, adolescence and young adulthood in relation to adult overweight and adiposity: the Fels Longitudinal Study. Int J Obes Relat Metab Disord 24, 16281635.
48. Kvaavik, E, Tell, GS & Klepp, KI (2003) Predictors and tracking of body mass index from adolescence into adulthood: follow-up of 18 to 20 years in the Oslo Youth Study. Arch Pediatr Adolesc Med 157, 12121218.
49. The, NS, Suchindran, C, North, KE et al. (2010) Association of adolescent obesity with risk of severe obesity in adulthood. JAMA 304, 20422047.
50. Wang, LY, Chyen, D, Lee, S et al. (2008) The association between body mass index in adolescence and obesity in adulthood. J Adolesc Health 42, 512518.
51. Llewellyn, A, Simmonds, M, Owen, CG et al. (2016) Childhood obesity as a predictor of morbidity in adulthood: a systematic review and meta‐analysis. Obes Rev 17, 5667.
52. Park, MH, Falconer, C, Viner, RM et al. (2012) The impact of childhood obesity on morbidity and mortality in adulthood: a systematic review. Obes Rev 13, 9851000.
53. Narayan, KMV, Boyle, JP, Thompson, TJ et al. (2007) Effect of BMI on lifetime risk for diabetes in the US. Diabetes Care 30, 15621566.
54. Owen, CG, Martin, RM, Whincup, P et al. (2005) Effect of infant feeding on the risk of obesity across the life course: a quantitative review of published evidence. Pediatrics 115, 13671377.
55. Yan, J, Liu, L, Zhu, Y et al. (2014) The association between breastfeeding and childhood obesity: a meta-analysis. BMC Public Health 14, 1267.
56. Lin, SL, Leung, GM, Lam, TH et al. (2013) Timing of solid food introduction and obesity: Hong Kong’s ‘children of 1997’ birth cohort. Pediatrics 131, e1459e1467.
57. Wang, J, Wu, Y, Xiong, G et al. (2016) Introduction of complementary feeding before 4 months of age increases the risk of childhood overweight or obesity: a meta-analysis of prospective cohort studies. Nutr Res 36, 759770.


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