Assessment of Child and Adolescent Overweight and Obesity

Krebs, Nancy F.; Himes, John H.; Jacobson, Dawn; Nicklas, Theresa A.; Guilday, Patricia; Styne, Dennis M.

doi:10.1542/peds.2007-2329d

Cited by 805 publications

(754 citation statements)

References 362 publications

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“…In addition, the 7-day dietary diary, which we used to obtain information on energy intake, has not been fully validated in Greek adolescents. Given that the dietary energy intake in our study decreased across time, which is contrary to previous reports, 34 it is possible that methodological limitations in our assessment may mask a link between dietary factors and metabolic syndrome.…”

Section: Discussioncontrasting

confidence: 94%

Longitudinal preventive-screening cutoffs for metabolic syndrome in adolescents

et al. 2008

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Objective: To detect metabolic risk factor cutoff points in adolescence for the diagnosis of metabolic syndrome that develops at the age of 17 years (MS 17 ). Design: This study adopted a 6-year design incorporating four data collection time points (TPs). Volunteers were assessed prospectively at the ages of 12, 13, 14 and 17. Participants: A total of 210, 204, 198 and 187 schoolchildren volunteered at the first (TP 1 ¼ 12 years old), second (TP 2 ¼ 13 years old), third (TP 3 ¼ 14 years old) and fourth (TP 4 ¼ 17 years old) data collection TP, respectively. Measurements: At each data collection TP, anthropometrical, biological and lifestyle data were obtained. Identical protocols were used for each assessment conducted by the same trained investigators. Results: A total of 12% of the participants were diagnosed with MS 17 , the majority of them being boys (Po0.05). The prevalence of the syndrome increased directly with the degree of obesity. Using body mass index (BMI), adiposity and/or aerobic fitness levels in both genders, MS 17 could be correctly diagnosed as early as TP 1 . No such cutoff points were found for high-density lipoprotein cholesterol, triglycerides, blood pressure and fasting plasma glucose levels. Conclusion: With respect to the data presented, it has been established that the calculated longitudinal preventive-screening cutoffs allow successful diagnosis of metabolic syndrome in adolescents using BMI, adiposity or aerobic fitness levels in both sexes. Adoption of such pediatric guidelines may help mitigate future increase in the prevalence of metabolic syndrome.

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Section: Discussioncontrasting

confidence: 94%

Longitudinal preventive-screening cutoffs for metabolic syndrome in adolescents

et al. 2008

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“…In accordance with recommendations of the American Academy of Pediatrics expert panel on childhood obesity, and the Institute of Medicine, we assigned each participant to an obese stratum (X95th percentile), an overweight stratum (85th percentile to 94th percentile) or a normal stratum (o85th percentile). 15,16 risk of being bullied as observed by others 34 --36 or teased among school children with high BMI percentiles as observed by others? Were obese or overweight children more likely to be embarrassed to participate in physical activities and miss the school day to avoid physical education sessions?…”

Section: Discussionmentioning

confidence: 82%

“…In accordance with recommendations of the American Academy of Pediatrics expert panel on childhood obesity, and the Institute of Medicine, we assigned each participant to an obese stratum (X95th percentile), an overweight stratum (85th percentile to 94th percentile) or a normal stratum (o85th percentile). 15,16 Abbreviations: BMI, body mass index; NHANES, National Health Examination and Nutrition Survey; PIR, poverty index ratio. a The severe absenteeism was defined as 'missing 2 days or more per school month' .…”

Section: Resultsmentioning

confidence: 99%

“…BMI was calculated in kg m À2 and then converted to a sex-and agespecific BMI percentile value using a computerized formula derived from the Centers for Disease Control and Prevention 2000 Growth Charts. 14 In accordance with recommendations of the American Academy of Pediatrics expert panel on childhood obesity 15 and the Institute of Medicine, 16 we assigned each participant to an obese stratum (BMI 95th percentile), an overweight stratum (85th percentile to 94th percentile) or a normal-weight stratum (o 85th percentile).…”

Section: Measurements and Variable Definitionsmentioning

confidence: 99%

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Association between increased BMI and severe school absenteeism among US children and adolescents: findings from a national survey, 2005–2008

Raychowdhury

Tedders

et al. 2012

Int J Obes

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OBJECTIVE: School absenteeism may be an underlying cause of poor school performance among overweight and obese children. We examined the associations between school absenteeism and body mass index (BMI) in a nationally representative sample. DESIGN AND SUBJECTS: We analyzed the data of 1387 children (6--11 years) and 2185 adolescents (12--18 years), who completed an interview and anthropometric measurement as a part of the National Health and Nutrition Examination Survey, 2005Survey, --2008. The CDC 2000 growth chart was used to categorize BMI status, and the number of school days missed during the past 12 months was assessed by asking the proxies or interviewees. RESULTS: The prevalence of obesity and overweight were 18.96 ± 1.44% (s.e.) and 16.41 ± 0.78%, respectively, among study populations. The means of school days missed in the last 12 months were not statistically different between the normal-weight, overweight and obese groups, 3.79±0.56, 3.86±0.38 and 4.31±0.01 days, respectively. However, when 42 days missed per school month was defined as severe absence, the prevalence of severe absence were 1.57%, 2.99% and 4.94% respectively, among 6 --11-year-old children with normal, overweight and obese. The adjusted odds of severe school absence were 2.27 (95% confidence interval ¼ 0.64 --8.03) and 3.93 (1.55 --9.95), respectively, among overweight and obese children compared with normal-weight peers (P for trend test o0.01). No significant association was found among adolescents. CONCLUSION: Increased body weight is independently associated with severe school absenteeism in children but not adolescents. Future research is needed to determine the nature, and academic and social significance of this association.

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“…4 This decline is considered to be partly responsible for adolescent obesity, 5 which is likely to lead to greater health risk in adulthood. 6 Given that the prevalence of overweight or obesity in adolescents living in China's urban areas has been increasing dramatically since the early 1990s-and is now equivalent to the level of some developed countries 7 increasing participation in physical activity in youth is a public health priority.…”

Section: Introductionmentioning

confidence: 99%

Associations of Residential Density with Adolescents’ Physical Activity in a Rapidly Urbanizing Area of Mainland China

Liang

et al. 2009

J Urban Health

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In the context of recent social and economic transitions in China, lack of physical activity among adolescents is an emerging health risk, particularly so in rapidly expanding urban areas. Evidence from Western countries suggests that built environment attributes can influence the physical activity participation of young people, but whether or not this is the case for China is unknown. We recruited high school students from ten urban districts in Nanjing, Mainland China (n=2,375; mean age=13.9± 1.0 years old; 46% boys; survey response rate=89%). The outcome variable was selfreported recreational physical activity time; the primary explanatory variable was the residential density of the urban districts. Analysis was conducted using mixed-effects logistic regression models. After adjustment for potential confounding variables, including sedentary behavior and green space, there was a consistent and graduated association between residential density and physical activity; residential density was significantly negatively associated with recreational physical activity time for students from the higher tertile of residential density (OR; 95% CI=0.64; 0.42 to 0.97) compared to those from the lower tertile. The direction and magnitude of the negative association between residential density and physical activity was similar for boys and girls. It should be a public health priority to identify the particular urban environment attributes that can encourage and support young people's participation in physical activity.

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Assessment of Child and Adolescent Overweight and Obesity

Cited by 805 publications

References 362 publications

Longitudinal preventive-screening cutoffs for metabolic syndrome in adolescents

Longitudinal preventive-screening cutoffs for metabolic syndrome in adolescents

Association between increased BMI and severe school absenteeism among US children and adolescents: findings from a national survey, 2005–2008

Associations of Residential Density with Adolescents’ Physical Activity in a Rapidly Urbanizing Area of Mainland China

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