Pediatricians' weight assessment and obesity management practices
© Huang et al; licensee BioMed Central Ltd. 2009
Received: 13 March 2008
Accepted: 05 March 2009
Published: 05 March 2009
Clinician adherence to obesity screening guidelines from United States health agencies remains suboptimal. This study explored how personal and career demographics influence pediatricians' weight assessment and management practices.
A web-based survey was distributed to U.S. pediatricians. Respondents were asked to identify the weight status of photographed children and about their weight assessment and management practices. Associations between career and personal demographic variables and pediatricians' weight perceptions, weight assessment and management practices were evaluated using univariate and multivariate modeling.
3,633 pediatric medical providers correctly identified the weight status of children at a median rate of 58%. The majority of pediatric clinicians were white, female, and of normal weight status with more than 10 years clinical experience. Experienced pediatric medical providers were less likely than younger colleagues to correctly identify the weight status of pictured children and were also less likely to know and use BMI criteria for assessing weight status. General pediatricians were more likely than subspecialty practitioners to provide diverse interventions for weight management. Non-white and Hispanic general practitioners were more likely than counterparts to consider cultural approaches to weight management.
Pediatricians' perceptions of children's weight and their weight assessment and management practices are influenced by career and personal characteristics. Objective criteria and clinical guidelines should be uniformly applied by pediatricians to screen for and manage pediatric obesity.
Overweight in children is a public health concern in the United States (U.S.) with increasing prevalence rates among children of all ages and cultural backgrounds over the past two decades . Globally, it is estimated that 22 million children under the age of 5 are overweight . The associations between overweight in children and significant health morbidities [3–7] have resulted in national health campaigns urging medical providers' involvement in the detection and treatment of this growing epidemic.
Although the Department of Health and Human Services , the American Academy of Pediatrics  and the American Medical Association  strongly advocate the use of objective criteria for obesity detection among children, clinician adoption of these guidelines remains suboptimal [11–18] and BMI documentation rates vary widely, from 0.5%  to 52% . We sought to determine whether personal and career demographics influenced U.S. pediatricians' weight assessment and management practices. Our a priori hypothesis was that U.S. pediatricians' weight assessment and management practices are influenced by personal and career demographics.
Participants and Setting
The study was approved by the University of California, San Diego Human Research Protections Program (UCSD HRPP). Potential participants were identified via membership in a non-profit U.S. pediatric medical association consisting of general pediatricians, pediatric subspecialists, and ancillary pediatric medical care providers. Members were eligible if they had a valid email address and were directly involved in the healthcare of children.
Weight assessment and weight management practices of surveyed pediatricians (N = 3,633).
Weight status assessment method (%)
10 General appearance
3 Weight alone
21 Weight for height
64 Body mass index
2 Professional experience
Knowledge of NCHS criterion for overweight (%)
Knowledge of NCHS criterion for obese (%)
Frequency of calculating body mass index (%)
11 At all visits
35 Only at well-child visits
34 Only when concerned
9 Only after a certain age
Frequency of weight concern discussion with patients (%)
18 At every visit
17 Only at well-child visits
62 Only when concerned
1 Only after a certain age
Interventions provided for weight management to patients (%)
54 Physical Activity
17 Social Work
20 Support Groups
Consideration for Culture in Weight Management
The questionnaire consisted of 12 photographs of children in four age categories (3 photographs per category: infant, toddler (1–3 years), 4–6 years, and 10–12 years). Children were photographed in both the anteroposterior and lateral positions in their undergarments. Weight status for photographed children ≥ 2 years of age were defined according NCHS BMI-for-age and sex percentile definitions of underweight (≤ 5%), normal weight (5%< × < 85%), overweight (85% ≤ × < 95%) and obese (≤ 95%) . Children <2 years of age were similarly assigned weight status based on sex-specific weight-for-height percentiles and the following definitions: underweight (≤ 5%), normal weight (5%< × < 85%), overweight (85% ≤ × <95%) and obese (≤ 95%).
Racial response categories included: white, black, Hispanic, Asian, or other; for statistical analyses, these groups were collapsed according to white or non-white and Hispanic or non-Hispanic origins. Other variables were also collapsed into dichotomous categories, including: sex (male vs. female); number of family generations in the United States (≥ 2 vs. <2); participant weight status (overweight and obese vs. normal weight and underweight); and career experience (<5 vs. ≥ 5 years). Participant weight category was assigned according to NCHS BMI categorical definitions .
Characteristics of photographed children were coded as follows: child sex (male vs. female); child race (white, Hispanic, or non-white non-Hispanic); child age (infant or toddler vs. 4–6 or 10–14 years); and child weight status (overweight or obese vs. normal weight or underweight).
Responses for the photograph survey were coded as correct or incorrect and as underestimation vs. overestimation or correct. Pediatric medical provider ability to correctly identify the weight status of children was represented as the number of photographed children for whom weight status was correctly identified (out of 12). Ability to correctly identify the weight status of overweight or obese unrelated children was represented as the number of photographed overweight or obese children correctly identified (out of 7).
Weight assessment practices were dichotomously coded as follows: whether the survey participant correctly identified both NCHS definitions for overweight and obese or not, whether the participant used subjective or objective criteria to assess weight status, whether the participant plotted BMI on a regular or selective basis, and whether the participant discussed weight concerns on a regular or selective basis. Weight management practices were coded as follows: whether the survey participant offered patients the weight management service (i.e. dietary services) or not, and whether the participant considered cultural issues or not in his/her approach to weight management.
Only complete data from pediatricians who confirmed direct participation in the healthcare of children were entered into the analysis (N = 3,633). Demographic data were summarized using descriptive statistics. Univariate analyses of participants' ability to correctly identify children's weight status by selected factors were performed using ANOVA analyses. Multivariate regression analysis was then applied to identify predictors of medical providers' ability to correctly identify children's weight that were independently significant after adjusting for other variables. Only variables with significant associations (defined as p < 0.05) were kept in the final model.
Univariate GEE Logistic Regression Analyses of surveyed practitioners' ability to estimate the weight status of photographed unrelated children and Selected Characteristics of the Photographed Children.
Photographed Child Characteristics
OR (95% CI) (correct vs. incorrect)
OR (95% CI) (underestimate vs. correct or overestimate)
Age (4–6 years or 10–14 years vs. Infant or Toddler)
8.76 (8.17, 9.39)
0.07 (0.07, 0.08)
Race (white vs. Non-white, non-Hispanic)
0.23 (0.22, 0.24)
0.42 (0.39, 0.46)
Race (Hispanic vs. Non-white, Non-Hispanic)
0.60 (0.56, 0.64)
0.33 (0.30, 0.35)
Sex (Female vs. Male)
1.20 (1.15, 1.26)
1.39 (1.25, 1.55)
Weight Status (Overweight or obese vs. Normal weight or underweight)
0.16 (0.15, 0.17)
143 (116, 176)
Participants' weight assessment and management practices were analyzed by selected factors using logistic regression analysis. Odds ratios (OR's) were calculated to determine the likelihood of the examined outcome by selected factors.
Statistical analyses were performed on questionnaire responses using JMP 5.0 statistical software (Cary, NC) and the R statistical package version 2.6.1 [22, 23]. Significance for all analyses was set at p < 0.05.
Demographic data of surveyed pediatricians (N = 3,633).
Sex (M:F, %)
24.5 ± 4.0
Actual Weight status (based on self reported height and weight – %)
US Geographical Region (%)
# Family Generations in the United States (%)
79 Two or More
Professional Status (%)
Years Professional Experience (%)
16 <5 years
27 5–10 years
57 > 10 years
Surveyed pediatric medical providers were able to correctly identify weight status in 7 (6, 8) [median (interquartile range)] out of 12 of presented photographs. In univariate analyses, respondents who were female (p = 0.04) and had less professional experience (<5 years, p < 0.01) were more likely than category counterparts to correctly assess children's weight status based on appearance alone. In multivariate analysis, only fewer years of professional experience remained significantly associated with ability to correctly assess children's weight based on appearance alone (p = 0.015).
Surveyed medical providers correctly identified overweight and obesity in 3 (3, 4) out of 7 presented photographs of overweight or obese children. Pediatricians with less professional experience (p = 0.002) were more likely than category counterparts to correctly assess overweight and obesity as compared to category counterparts.
Pediatricians were more likely to correctly (versus incorrectly) assess the weight status of photographed children if the children were non-white, non-Hispanic, female, normal weight or underweight, and 4 years or older (Table 2; column 1). Practitioners were more likely to underestimate (versus correctly estimate or overestimate) the weight status of photographed children if children were female, non-white, non-Hispanic, and infants or toddlers (Table 2, column 2).
Weight assessment and management practices
Univariate Analyses of surveyed practitioners' weight assessment practices and Selected Characteristics of the Practitioners
Use of Objective Criteria to Assess Weight
Knowledge of NCHS definitions of weight status
Calculation of BMI at every visit
Calculation of BMI at well-child visits only
Sex (Male vs. Female)
0.58 (0.48, 0.72)
0.76 (0.66, 0.88)
1.01 (0.83, 1.25)
0.78 (0.69, 0.89)
Race (white vs. Non-white)
0.83 (0.65, 1.08)
1.03 (0.86, 1.22)
0.76 (0.6, 0.96)
1.07 (0.92, 1.26)
Ethnicity (Non-Hispanic vs. Hispanic)
0.52 (0.28, 0.96)
1.11 (0.79, 1.56)
0.74 (0.47, 1.14)
0.88 (0.65, 1.20)
Weight Status (Overweight or Obese vs. Normal weight or Underweight)
0.81 (0.66, 1)
0.81 (.70, 0.94)
0.88 (0.71, 1.09)
0.86 (0.75, 0.98)
Professional Experience (<5 years vs. ≥ 5 years)
1.73 (1.25, 2.40)
1.65 (1.38, 1.98)
1.27 (0.98, 1.65)
1.39 (1.18, 1.67)
Subspecialty Status (Generalist vs. Subspecialist)
3.18 (2.57, 3.92)
1.48 (1.24, 1.76)
0.52 (0.42, 0.65)
3.57 (3, 4.17)
Univariate Analyses of surveyed practitioners' weight management practices and Selected Characteristics of the Practitioners
Provision of Nutritional Intervention
Provision of Counseling
Provision of Support Groups
Provision of Social Work Intervention
Provision of Physical Activity Intervention
Cultural Considerations in Weight Management Approach
Sex (Male vs. Female)
Race (white vs. Non-white)
Ethnicity (Non-Hispanic vs. Hispanic)
Professional Experience (<5 years vs. ≥ 5 years)
Subspecialty Status (Generalist vs. Subspecialist)
To our knowledge, we present the largest study evaluating pediatricians' weight perceptions of children and their weight assessment and management practices. Our study also assessed a number of personal and career demographic variables in order to control for potential confounding factors. The implications of our findings are discussed below.
In our U.S. sample, pediatricians were not proficient at discerning children's weight status based on appearance alone, especially among children who were overweight or obese. In comparison to parents who took the same survey, pediatricians as a group demonstrated the exact same accuracy rate at weight status identification as parents . Practitioners also demonstrated weight perception biases according to the characteristics of the children evaluated. Fortunately, only a minority of pediatricians reported using subjective criteria to judge weight status in children.
Use of BMI criteria for weight screening among surveyed pediatricians was suboptimal. Less than half of surveyed pediatricians knew the NCHS definitions for pediatric overweight and obesity, and a minority of physicians reported calculating BMI on a routine basis (either at well-child care visits or at all visits). Our findings validate prior studies documenting low BMI screening among pediatricians [17, 26].
Surveyed physicians dispersed weight-related interventions based on level of concern. Other studies also demonstrate discretionary weight-related counseling by physicians [12, 17]. Universal screening for pediatric overweight and obesity would increase weight-related counseling by physicians by improving identification of overweight and obesity. In our cohort, physicians who reported regular screening for pediatric obesity at well-child care visits were more likely to counsel on weight than physicians who did not. Recent guidelines also advocate that weight-related issues such as diet and physical activity be discussed regardless of weight status .
Our data indicate that practitioner characteristics need to be addressed when developing interventions aimed at improving provider compliance with obesity management recommendations. Both weight assessment and weight management practices varied according to physician characteristics. Our finding that overweight practitioners were less likely to know weight assessment definitions and routinely use BMI to assess weight validates prior data demonstrating reduced obesity recognition by overweight vs. normal weight practitioners . Younger practitioners' familiarity with and use of BMI screening for weight assessment may reflect more recent training and formal review of current weight assessment guidelines. Cultural considerations in weight management by junior, non-white, and Hispanic health practitioners may reflect greater acceptance of and/or personal familiarity with cultural issues. Lastly, increased use of multidisciplinary approaches for weight management by general vs. subspecialty pediatric health professionals may reflect greater physician awareness of weight-related issues resulting from more frequent and intimate contact in the primary care vs. subspecialty setting. Given the chronicity of weight management, interdisciplinary coordination is often required to successfully accomplish health-related goals.
The findings of this study are subject to a number of limitations. Most importantly, study data were retrieved from a small representation of currently practicing providers who interact with children. We nevertheless present data from the largest cohort to date of U.S. pediatric medical practitioners. In addition, we chose to determine weight status from self-reported parameters. However, prior studies have shown that self-reported weight and height are reliable for determining weight status, particularly among physicians [28, 29]. Thirdly, weight assessment and management practices were self-reported by surveyed practitioners. However, in the case of response bias, we would expect that surveyed practitioners would over-report practices known to comply with expert recommendations; therefore, actual compliance with expert recommendations may in fact be even more suboptimal than documented in this report. Lastly, lack of provision of weight management resources by providers may have reflected poor availability of resources. Nevertheless, we would have expected that resources would not vary by physician characteristics as was demonstrated in our cohort.
In conclusion, we demonstrate that U.S. pediatricians' weight assessment and management practices are associated with personal and career demographics. U.S. clinicians who regularly evaluate children should use objective weight screening methods and criteria. Similarly, pediatricians should adopt expert clinical guidelines to minimize personal bias in the management of weight.
The authors gratefully acknowledge Van Ong who helped recruit study participants. We also wish to thank our research volunteers and the Resthaven Children's Health Fund for grant support.
- Ogden CL, Flegal KM, Carroll MD, Johnson CL: Prevalence and trends in overweight among US children and adolescents, 1999–2000. Jama. 2002, 288 (14): 1728-1732. 10.1001/jama.288.14.1728.View ArticlePubMedGoogle Scholar
- Global Strategy on Diet, Physical Activity and Health: Obesity and Overweight. [http://www.who.int/dietphysicalactivity/publications/facts/obesity/en/]
- Sinha R, Fisch G, Teague B, Tamborlane WV, Banyas B, Allen K, Savoye M, Rieger V, Taksali S, Barbetta G, et al: Prevalence of impaired glucose tolerance among children and adolescents with marked obesity. N Engl J Med. 2002, 346 (11): 802-810. 10.1056/NEJMoa012578.View ArticlePubMedGoogle Scholar
- Mallory GB, Fiser DH, Jackson R: Sleep-associated breathing disorders in morbidly obese children and adolescents. J Pediatr. 1989, 115 (6): 892-897. 10.1016/S0022-3476(89)80738-3.View ArticlePubMedGoogle Scholar
- Lavine JE, Schwimmer JB: Pediatric initiatives within the Nonalcoholic Steatohepatitis-Clinical Research Network (NASH CNR). J Pediatr Gastroenterol Nutr. 2003, 37 (3): 220-221. 10.1097/00005176-200309000-00002.View ArticlePubMedGoogle Scholar
- Sorof J, Daniels S: Obesity hypertension in children: a problem of epidemic proportions. Hypertension. 2002, 40 (4): 441-447. 10.1161/01.HYP.0000032940.33466.12.View ArticlePubMedGoogle Scholar
- Schwimmer JB, Burwinkle TM, Varni JW: Health-related quality of life of severely obese children and adolescents. Jama. 2003, 289 (14): 1813-1819. 10.1001/jama.289.14.1813.View ArticlePubMedGoogle Scholar
- Barlow SE, Dietz WH: Obesity evaluation and treatment: Expert Committee recommendations. The Maternal and Child Health Bureau, Health Resources and Services Administration and the Department of Health and Human Services. Pediatrics. 1998, 102 (3): E29-10.1542/peds.102.3.e29.View ArticlePubMedGoogle Scholar
- Barlow SE: Expert committee recommendations regarding the prevention, assessment, and treatment of child and adolescent overweight and obesity: summary report. Pediatrics. 2007, 120 (Suppl 4): S164-192. 10.1542/peds.2007-2329C.View ArticlePubMedGoogle Scholar
- Expert Committee Recommendations on the Assessment, Prevention, and Treatment of Child and Adolescent Overweight and Obesity. [http://www.ama-assn.org/ama1/pub/upload/mm/433/ped_obesity_recs.pdf]
- Riley MR, Bass NM, Rosenthal P, Merriman RB: Underdiagnosis of pediatric obesity and underscreening for fatty liver disease and metabolic syndrome by pediatricians and pediatric subspecialists. J Pediatr. 2005, 147 (6): 839-842. 10.1016/j.jpeds.2005.07.020.View ArticlePubMedGoogle Scholar
- O'Brien SH, Holubkov R, Reis EC: Identification, evaluation, and management of obesity in an academic primary care center. Pediatrics. 2004, 114 (2): e154-159. 10.1542/peds.114.2.e154.View ArticlePubMedGoogle Scholar
- Mabry IR, Clark SJ, Kemper A, Fraser K, Kileny S, Cabana MD: Variation in establishing a diagnosis of obesity in children. Clin Pediatr (Phila). 2005, 44 (3): 221-227.View ArticleGoogle Scholar
- Dorsey KB, Wells C, Krumholz HM, Concato JC: Diagnosis, evaluation, and treatment of childhood obesity in pediatric practice. Arch Pediatr Adolesc Med. 2005, 159 (7): 632-638. 10.1001/archpedi.159.7.632.View ArticlePubMedGoogle Scholar
- Dilley KJ, Martin LA, Sullivan C, Seshadri R, Binns HJ: Identification of overweight status is associated with higher rates of screening for comorbidities of overweight in pediatric primary care practice. Pediatrics. 2007, 119 (1): e148-155. 10.1542/peds.2005-2867.View ArticlePubMedGoogle Scholar
- Cook S, Weitzman M, Auinger P, Barlow SE: Screening and counseling associated with obesity diagnosis in a national survey of ambulatory pediatric visits. Pediatrics. 2005, 116 (1): 112-116. 10.1542/peds.2004-1517.View ArticlePubMedGoogle Scholar
- Barlow SE, Bobra SR, Elliott MB, Brownson RC, Haire-Joshu D: Recognition of childhood overweight during health supervision visits: Does BMI help pediatricians?. Obesity (Silver Spring). 2007, 15 (1): 225-232. 10.1038/oby.2007.535.View ArticleGoogle Scholar
- Klein JD, Sesselberg TS, O'Connor K, Cook S, Johnson M, Washington R, Krebs N, Homer C: Childhood obesity practices of US pediatricians in 2006. Pediatric Academic Societies: 2007; Toronto, Canada. 2007Google Scholar
- Kuczmarski RJ, Ogden CL, Guo SS, Grummer-Strawn LM, Flegal KM, Mei Z, Wei R, Curtin LR, Roche AF, Johnson CL: 2000 CDC Growth Charts for the United States: methods and development. Vital and health statistics. 2002, 1-190. 246Google Scholar
- Kuczmarski RJ, Flegal KM: Criteria for definition of overweight in transition: background and recommendations for the United States. Am J Clin Nutr. 2000, 72 (5): 1074-1081.PubMedGoogle Scholar
- Zeger SL, Liang KY: Longitudinal data analysis for discrete and continuous outcomes. Biometrics. 1986, 42 (1): 121-130. 10.2307/2531248.View ArticlePubMedGoogle Scholar
- R Development Core Team: R: A language and environment for statistical computing. 2006, Vienna, Austria: R Foundation for Statistical ComputingGoogle Scholar
- Carey VJ: gee: Generalized Estimation Equation Solver. R package version 4.13-10. 2002Google Scholar
- Eysenbach G: Improving the quality of Web surveys: the Checklist for Reporting Results of Internet E-Surveys (CHERRIES). Journal of medical Internet research. 2004, 6 (3): e34-10.2196/jmir.6.3.e34.View ArticlePubMedPubMed CentralGoogle Scholar
- Huang JS, Becerra K, Oda T, Walker E, Xu R, Donohue M, Chen I, Curbelo V, Breslow A: Parental ability to discriminate the weight status of children: results of a survey. Pediatrics. 2007, 120 (1): e112-119. 10.1542/peds.2006-2143.View ArticlePubMedGoogle Scholar
- Dorsey KB, Wells C, Krumholz HM, Concato J: Diagnosis, evaluation, and treatment of childhood obesity in pediatric practice. Arch Pediatr Adolesc Med. 2005, 159 (7): 632-638. 10.1001/archpedi.159.7.632.View ArticlePubMedGoogle Scholar
- Reilly JM: Are obese physicians effective at providing healthy lifestyle counseling?. American family physician. 2007, 75 (5): 738-741PubMedGoogle Scholar
- McAdams MA, Van Dam RM, Hu FB: Comparison of self-reported and measured BMI as correlates of disease markers in US adults. Obesity (Silver Spring). 2007, 15 (1): 188-196. 10.1038/oby.2007.504.View ArticleGoogle Scholar
- Klag MJ, He J, Mead LA, Ford DE, Pearson TA, Levine DM: Validity of physicians' self-reports of cardiovascular disease risk factors. Ann Epidemiol. 1993, 3 (4): 442-447.View ArticlePubMedGoogle Scholar
- The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2431/9/19/prepub
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