全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...
ISRN Obesity  2013 

Large Clothing Size in Children Is Associated with High Body Mass Index and Clustering of Medical Comorbidities

DOI: 10.1155/2013/582967

Full-Text   Cite this paper   Add to My Lib

Abstract:

Background. Since most people are aware of their clothing size (CS), this prospective study explored the potential utility of CS as a proxy for body size and as a predictor of incident obesity-related health conditions in children. Methods. This was a prospective, cross-sectional study of 725 children aged 6–18 yr. We collected clinical, anthropometric, and sartorial data on all study subjects. Parents reported their children’s usual CS. This was compared with US clothing chart for children. Based on this we determined whether a child’s CS was appropriate or large for age. Results. The prevalence of overweight/obese was 31.4%. Among the study subjects, 36% usually wore large CS. Children who wore large CS were more likely to be overweight/obese compared to those in the normal CS group (OR?=?5.6; 95% CI?=?4.0–8.0, ). Similarly, large CS was associated with higher rates of incident asthma ( ), obstructive sleep apnea ( ), habitual snoring ( ), and elevated preoperative blood pressure ( ). Conclusion. CS in children is associated with higher indices of adiposity and increased rates of obesity-related comorbidities. 1. Introduction Obesity has reached epidemic proportions in American adults and children and in most parts of the developed world [1, 2]. Childhood obesity has indeed become one of the foremost issues in contemporary biomedical research particularly because of its importance in predicting adult overweight and obesity as well as its association with various cardiovascular risk factors [2]. The most common descriptor of obesity (used for health promotion information and risk stratification) is the body mass index (BMI), defined as an individual’s weight in kilograms divided by the square of their height in meters (BMI =??kg/m2) [3, 4]. It is however becoming increasingly clear from clinical and epidemiologic studies that BMI may not be an accurate proxy for obesity-associated risks [5–7]. This is because BMI does not specify fat distribution and compared to other indices of adiposity, it correlates poorly with visceral (central) obesity, which tends to be more pathogenic given its close association with cardiovascular and metabolic risks [8–10]. Furthermore, central adiposity is associated with severe obstructive sleep apnea (OSA) in adults [11] and central apnea with severe nocturnal oxygenation desaturation in children [12, 13]. Due to the many limitations of BMI as a risk stratifier, other indices of adiposity are being explored. Waist circumference (WC) measurement is the most commonly used measure of central adiposity and has become the

References

[1]  C. L. Ogden, M. D. Carroll, L. R. Curtin, M. A. McDowell, C. J. Tabak, and K. M. Flegal, “Prevalence of overweight and obesity in the United States, 1999–2004,” Journal of the American Medical Association, vol. 295, no. 13, pp. 1549–1555, 2006.
[2]  World Health Organization, Obesity: Preventing and Managing the Global Epidemic. Report of a WHO Consultation on Obesity, WHO, Geneva, Switzerland, 1998.
[3]  J. J. Reilly, “Diagnostic accuracy of the BMI for age in paediatrics,” International Journal of Obesity (London), vol. 30, no. 4, pp. 595–597, 2006.
[4]  T. J. Cole, M. C. Bellizzi, K. M. Flegal, and W. H. Dietz, “Establishing a standard definition for child overweight and obesity worldwide: international survey,” British Medical Journal, vol. 320, no. 7244, pp. 1240–1243, 2000.
[5]  J. Gómez-Ambrosi, C. Silva, J. C. Galofré et al., “Body mass index classification misses subjects with increased cardio-metabolic risk factors related to elevated adiposity,” International Journal of Obesity (London), vol. 36, pp. 286–294, 2012.
[6]  A. M. Nevill, A. D. Stewart, T. Olds, and R. Holder, “Relationship between adiposity and body size reveals limitations of BMI,” American Journal of Physical Anthropology, vol. 129, no. 1, pp. 151–156, 2006.
[7]  S. B. Heymsfield, R. Scherzer, A. Pietrobelli, C. E. Lewis, and C. Grunfeld, “Body mass index as a phenotypic expression of adiposity: quantitative contribution of muscularity in a population-based sample,” International Journal of Obesity, vol. 33, no. 12, pp. 1363–1373, 2009.
[8]  C. N. Lumeng and A. R. Saltiel, “Inflammatory links between obesity and metabolic disease,” Journal of Clinical Investigation, vol. 121, no. 6, pp. 2111–2117, 2011.
[9]  P. T. Katzmarzyk, S. R. Srinivasan, W. Chen, R. M. Malina, C. Bouchard, and G. S. Berenson, “Body mass index, waist circumference, and clustering of cardiovascular disease risk factors in a biracial sample of children and adolescents,” Pediatrics, vol. 114, no. 2, pp. e198–e205, 2004.
[10]  S. R. Daniels, P. R. Khoury, and J. A. Morrison, “Utility of different measures of body fat distribution in children and adolescents,” American Journal of Epidemiology, vol. 152, no. 12, pp. 1179–1184, 2000.
[11]  R. Grunstein, I. Wilcox, T. S. Yang, Y. Gould, and J. Hedner, “Snoring and sleep apnoea in men: association with central obesity and hypertenslon,” International Journal of Obesity and Related Metabolic Disorders, vol. 17, no. 9, pp. 533–540, 1993.
[12]  S. L. Verhulst, N. Schrauwen, D. Haentjens et al., “Sleep-disordered breathing in overweight and obese children and adolescents: prevalence, characteristics and the role of fat distribution,” Archives of Disease in Childhood, vol. 92, no. 3, pp. 205–208, 2007.
[13]  Y. K. Wing, S. H. Hui, W. M. Pak et al., “A controlled study of sleep related disordered breathing in obese children,” Archives of Disease in Childhood, vol. 88, no. 12, pp. 1043–1047, 2003.
[14]  J. C. Seidell, “Waist circumference and waist/hip ratio in relation to all-cause mortality, cancer and sleep apnea,” European Journal of Clinical Nutrition, vol. 64, no. 1, pp. 35–41, 2010.
[15]  I. S. Okosun, Y. Liao, C. N. Rotimi, T. E. Prewitt, and R. S. Cooper, “Abdominal adiposity and clustering of multiple metabolic syndrome in White, Black and Hispanic Americans,” Annals of Epidemiology, vol. 10, no. 5, pp. 263–270, 2000.
[16]  J. N. Morris, J. A. Heady, and P. A. B. Raffle, “Physique of London busmen. Epidemiology of uniforms,” The Lancet, vol. 268, no. 6942, pp. 569–570, 1956.
[17]  D. S. Battram, C. Beynon, and M. He, “The reliability and validity of using clothing size as a proxy for waist circumference measurement in adults,” Applied Physiology, Nutrition and Metabolism, vol. 36, no. 2, pp. 183–190, 2011.
[18]  T. S. Han, E. Gates, E. Truscott, and M. E. J. Lean, “Clothing size as an indicator of adiposity, ischaemic heart disease and cardiovascular risks,” Journal of Human Nutrition and Dietetics, vol. 18, no. 6, pp. 423–430, 2005.
[19]  I. S. Okosun, J. M. Boltri, M. P. Eriksen, and V. A. Hepburn, “Trends in abdominal obesity in young people: United states 1988–2002,” Ethnicity and Disease, vol. 16, no. 2, pp. 338–344, 2006.
[20]  “Children’s Size Chart for Clothes,” 2011, http://www.childrenssizechart.com/.
[21]  O. O. Nafiu, C. Burke, J. Lee, T. Voepel-Lewis, S. Malviya, and K. K. Tremper, “Neck circumference as a screening measure for identifying children with high body mass index,” Pediatrics, vol. 126, no. 2, pp. e306–e310, 2010.
[22]  M. L. Hansen, P. W. Gunn, and D. C. Kaelber, “Underdiagnosis of hypertension in children and adolescents,” Journal of the American Medical Association, vol. 298, no. 8, pp. 874–879, 2007.
[23]  I. A. Perez and S. L. D. Ward, “The snoring child,” Pediatric Annals, vol. 37, no. 7, pp. 465–470, 2008.
[24]  R. J. Kuczmarski, C. L. Ogden, S. S. Guo et al., “2000 CDC Growth Charts for the United States: methods and development,” Vital and Health Statistics. Series 11, no. 246, pp. 1–190, 2002.
[25]  J. A. Hanley and B. J. McNeil, “The meaning and use of the area under a receiver operating characteristic (ROC) curve,” Radiology, vol. 143, no. 1, pp. 29–36, 1982.
[26]  D. W. Hosmer, T. Hosmer, S. Le Cessie, and S. Lemeshow, “A comparison of goodness-of-fit tests for the logistic regression model,” Statistics in Medicine, vol. 16, no. 9, pp. 965–980, 1997.
[27]  L. A. E. Hughes, L. J. Schouten, R. A. Goldbohm, P. A. van den Brandt, and M. P. Weijenberg, “Self-reported clothing size as a proxy measure for body size,” Epidemiology, vol. 20, no. 5, pp. 673–676, 2009.

Full-Text

comments powered by Disqus

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133

WeChat 1538708413