Examining Body Mass Index in an Urban Core Population

Abstract

Background. Childhood obesity is commonly encountered in the primary care office and disproportionately affects those from low income or minority backgrounds. Objective. To determine how accurately primary care clinicians in an urban setting identified patients with body mass indices (BMIs) at or above the 95th percentile for age and to determine which obesity treatment strategies are used. Materials and Methods. The study population consisted of school-aged, inner-city children with a BMI at or above the 95th percentile for age whose charts were made available for data collection by retrospective chart review. Results. A total of 158 patient medical charts were reviewed. Of these, 90 (57%) patients failed to be identified by the provider as having an elevated BMI. Obesity treatment was initiated in only 68 (43%) of these patients. Conclusions. Providers are not effectively recognizing childhood obesity and are not consistently implementing effective obesity treatment strategies.

Keywords

childhood obesity treatment of childhood obesity childhood obesity in minorities exercise nutrition cultural differences comorbid conditions in childhood obesity

Introduction

Over the past three decades, childhood obesity has been a growing challenge for patients and health care professionals. It is estimated that 40% of children in North America were overweight or obese in 2010.¹ The goal of treatment for obese children is to establish permanent healthy lifestyle changes, leading to improved long-term physical health.²

The primary care setting is an ideal place to initiate and monitor treatment for patients at risk of obesity. Beginning a treatment plan during primary care visits has been shown to be effective in establishing healthy habits.³ Pediatricians should intervene early by screening for unhealthy weight trajectories to prevent obesity from developing.⁴ The American Medical Association Expert Committee outlines several stages of treatment for obesity, including obesity prevention and maintaining a healthy lifestyle. Recommended treatment strategies include discussing a diet with balanced macronutrient intake, monitoring behavior through use of activity logs, reducing television time, and increasing physical activity.⁵

Though the importance of early intervention and treatment is well established, limited research has been recently published on how well the current guidelines for screening and treatment are followed in the primary care office. The goal of this study was to determine the frequency with which children from the Score 1 for Health program with body mass indices (BMIs) at or above the 95th percentile for age were screened for elevated BMI and/or received obesity-related treatment during one or more visits to a primary care provider. We also wished to evaluate what kinds of obesity treatment strategies were initiated in these patients with an elevated BMI.

Methods

The Score 1 for Health program, in association with the Kansas City University of Medicine and Biosciences, provides health screenings for children in kindergarten through fifth grade throughout the urban core of Kansas City. The database for Score 1 for Health contains longitudinal health information from the screenings of nearly 13 000 children per year. The Score 1 for Health database was chosen because students in the urban core of Kansas City are composed of multiple ethnicities and socioeconomic status.⁶

Data for the Score 1 for Health database are generated at annual health screenings of children aged 5 to 12 years at 53 elementary schools in the greater Kansas City area. Each child is screened for height and weight measurements, and BMI is calculated as a relative percentile for age based on the standards set by the Centers for Disease Control and Prevention.⁶ BMI percentile for age was chosen to reflect how overweight the child is, because BMI is a moderately sensitive and specific indicator of excess body fat in children greater than or equal to the 95th percentile.⁷

Participant Selection

Data were obtained from the Score 1 for Health database for students screened in academic years 2007 through 2010. To be included in this study, a child must have had a calculated BMI above the 95th percentile for age during at least two of the three study years. Several primary care clinics located in close proximity to the schools served by Score 1 for Health were contacted and given the opportunity to participate in the study. De-identified database records containing only the patient’s birth date and no other personal health information were matched with participating clinic medical records by birth date. The medical records of these patients were collected and reviewed and became the study population.

Data Abstraction Methods

Chart review of those children meeting the inclusion criteria examined documentation for three different types of data: positive identification of an elevated BMI, total number of clinic visits, and therapies implemented by the physician during each visit. Each chart was assessed for whether or not the patient’s BMI status was explicitly documented. It was also noted if the patient received some form of therapy for the elevated BMI during each visit, regardless of whether or not an elevated BMI status was documented. The types of obesity-related therapies that were assessed included nutritional counseling by the physician; referral to a dietitian; dietitian counseling during the visit; exercise history taken; nutritional history taken; whether the child was advised to increase their level of activity or exercise; whether a food or activity log was prescribed; and whether the physician advised a limitation to the child’s “screen time,” defined as time spent in front of a television or computer. The following disease states have been associated with elevated BMI and presence of these disease states were evaluated on chart review: hypertension,^8,9 type 2 diabetes,^10,11 acanthosis nigricans,¹² lower extremity musculoskeletal disorders due to slipped capital femoral epiphysis, fractures and Blount’s disease,^13-16 depression,^17,18 asthma,¹⁹ acid reflux,²⁰ and sleep apnea.²¹ Race, as reported by the patient, was also recorded.

To provide additional insight into the data found following the chart reviews, primary care providers from clinics participating in chart review as well as academic faculty at our institution were offered surveys and face-to-face interviews. Interviews and surveys were conducted after chart review and did not influence how the obesity treatment was provided, treated, or documented. The surveys provided for an additional, quantitative analysis to the data obtained from the medical records and consisted of predetermined statements. Each statement was ranked by the physician, using a 5-point Likert-type scale, regarding their level of agreement or disagreement with each statement. The interview process provided strictly qualitative information but allowed for supplemental information to the responses provided in the surveys, as well as provided an outlet for the primary care providers to freely give their input on the topic of childhood obesity and its challenges.

Results

A total of 39 568 children were screened by Score 1 for Health during the academic years 2007 to 2010. Of these, 8773 (22.2%) children were determined to have a BMI at or above the 95th percentile for age (Table 1). Additionally, 1944 children (22.2%) had two or more BMI values above the 95th percentile. The medical charts of the 1944 children with two or more BMI screening values were searched for by birth date at local physicians’ offices. Of the six local physician’s offices invited to participate in the study, two agreed to participate. The medical charts for 158 (8.1%) obese children were matched by birth date at these primary care settings and were reviewed. The majority of the study population (n = 112, 70.9%) identified themselves as being of Hispanic origin (Table 2). Although all the children in the study population where known to be at or above the 95th percentile for BMI, less than half (n = 68; 43.0%) were identified in their medical record as having an elevated BMI (Table 3). Fortunately, a majority of these medical record–identified obese children were prescribed obesity-related treatment (n = 61/68, 89.7%). The unfortunate interpretation to this finding is the fact that the majority of the known obese children did not get identified in their medical records as being obese (n = 90, 57.0%). Although there may be several potential rationales for this omission in documentation, one might anticipate that their physical presence with the clinician might still invoke the need for obesity-related recommendations and treatment. Unfortunately, the majority of the study population (n = 97, 61.4%) did not receive obesity-related therapy, even though 7 (7.2%) obese children were documented in their medical record as being obese or having an elevated BMI. Not surprisingly, no child was offered obesity treatment if their medical record did not indicate concurrent elevated BMI (albeit an omission on the weight-related designation).

Table 1.

Population Screened by Score 1 for Health (by Academic Year) and Frequency of Body Mass Index (BMI) ≥95th Percentile for Age

Academic Year	Screened (n)	BMI ≥95th Percentile; n (%)
2007-2008	13 153	2827 (21.5)
2008-2009	12 796	2829 (22.1)
2009-2010	13 619	3117 (22.9)
Total	39 568	8773 (22.2)

Table 2.

Frequency of Self-Reported Race

Race	n (%)
Hispanic	112 (70.9)
Black	8 (5.1)
Multiracial	6 (3.8)
White	1 (0.6)
Not reported	31 (19.6)
Total	158 (100)

Table 3.

Frequency of Therapy Initiation in Patients With and Without an Elevated Body Mass Index (BMI) noted on Screening

Elevated BMI Noted	Therapy Initiated		Total
Elevated BMI Noted	No	Yes	Total
No	90	0	90
Yes	7	61	68
Total	97	61	158

Data revealed that the proportion of notations of a provider-identified elevated BMI increased as the child’s visit frequency increased (Table 4). A total of 83 patients visited the physician between one and five times, with 23 (27.7%) of these children receiving an elevated BMI identification in their chart. A total of 25 children visited the physician 15 or more times, with 18 (72%) of these children receiving an elevated BMI identification. When obesity-related treatment was begun, an average of three treatment strategies was encouraged at one time. Nutritional counseling by the physician was used the most frequent amount of times for weight management (n = 49, 35%), followed closely by simply taking a nutritional history (n = 42, 30%). Activity or food logs were not used in any of the children in our study population (Table 5). The most commonly occurring obesity-associated comorbidity noted in the study population was asthma (n = 18, 41.9% of all comorbidities listed), followed by type 2 diabetes mellitus (n = 13, 30.3% of all comorbidities listed), with no children being documented as having depression (Table 6).

Table 4.

Frequency of Patient Screening Visits and Documentation of Elevated Body Mass Index (BMI)

Screening Visits	n	Elevated BMI Noted; n (%)
1-5	83	23 (27.7)
6-10	37	19 (51.3)
11-14	13	8 (61.5)
≥15	25	18 (72.0)
Total	158	68 (43.0)

Table 5.

Frequency of Specific Therapies Recommended

Therapy	n (%)
Nutritional history taken	42 (30.0%)
Nutrition counseling by physician	49 (35.0%)
Nutrition counseling by dietician	13 (9.3%)
Exercise increase	17 (12.1%)
Exercise history	13 (9.3%)
Limit screen^a time	6 (4.3%)
Activity or food log	0 (0.0%)
Total number of interventions	140 (100 %)
Total patients with therapy recommended	61
Mean number of therapies per patient	3

Self-reported time spent in front of a television or computer per day.

Table 6.

Frequency of Specific Comorbidities

Comorbidity	n (%)
Asthma	18 (41.9)
Type 2 diabetes mellitus	13 (30.3)
Hypertension	5 (11.6)
Lower musculoskeletal	5 (11.6)
Sleep apnea	1 (2.3)
Acid reflux	1 (2.3)
Depression	0 (0)
Total comorbidities	43 (100)

Ten health care professionals were interviewed and surveyed to explain how they managed the care of their obese patients, as well as any perceived barriers to effective treatment. Almost all clinicians agreed that BMI is an important factor in assessing a patient’s overall health. Most also realized that other health conditions may be directly related to obesity. Those surveyed also expressed concern with compliance, even if BMI counseling was offered. Practitioners most strongly agreed with the statement “It is important to address BMI when a child presents to my clinic” (mean score = 4.86 out of 5) and least likely to agree with the statement “When I do offer weight loss counseling or give advice about any of the above suggestions, I feel that my patients are compliant” (mean score = 2.15 out of 5; Table 7).

Table 7.

Physician Survey Items^a and Responses

Question	Mean (SD)	Mode	Min/Max
“Most of the Score 1 referrals that I treat are patients who present with an elevated BMI (either in combination with, or individual from, any other health problems).”	3 (1.53)	1,3,4^b	1/5
“Patients who present to me with an elevated BMI also have coinciding health issues.”	3.57 (1.27)	2,4,5	2/5
“I feel that many of these comorbidities are due to the patients’ elevated BMI.”	4.43 (0.54)	4	4/5
“Coinciding health issues such as hypertension and diabetes take precedence over BMI when in the office visit of children referred to me by Score 1 for Health.”	3 (1.16)	4	1/4
“Because of coinciding health issues, I sometimes find it difficult to address BMI directly.”	3.29 (1.25)	2,4	2/5
“When I do offer weight loss counseling or give advice about any of the above^c suggestions, I feel that my patients are compliant.”	2.15 (0.9)	2	1/4
“It is important to address elevated BMI when a child presents to my practice.”	4.86 (0.38)	5	4/5

Abbreviations: SD, standard deviation; Min/Max, minimum/maximum; BMI, body mass index.

Survey responses were based on a 5-point Likert-type scale: strongly agree = 5, agree = 4, neither agree nor disagree = 3, disagree = 2, strongly disagree = 1.

More than one number represents multimodal.

Treatment suggestions offered in survey included the following: using a food log, using an activity log or history of physical activity, monitoring dietary consumption of sugary drinks, limiting time spent watching television or working on the computer, monitoring consumption of sugary snacks, or “other” (specifically defined by respondent).

Discussion

Pediatric obesity is an epidemic in America, and many barriers to recognition and treatment must be addressed before there will be adequate impact on this growing disease. In addition to the social stigma that comes with being overweight in childhood, there are a number of medical illnesses associated with obesity that can contribute to the overall declining health of young people. With all the associated medical conditions and their overwhelming prevalence in the United States, it begs the question: is childhood obesity being treated adequately in the United States, and if not, what are some of the barriers that practitioners face in identifying obesity and implementing therapeutic interventions for its effective treatment?

There are several plausible answers to the question. One of the first problems in treating overweight children in our study population seemed to be as simple as overcoming language barriers; for example, English-speaking practitioners needing to communicate with Spanish-speaking parents. With difficulties in communication, dietary counseling may not be possible.²² Information gathered during the interview portion of this study suggested that, “It would be helpful if we could have informational resources at our clinic about a healthy diet printed in Spanish as well as English,” (Interview, Nurse Practitioner).

Additionally, ethnic points of view about what constitutes an “overweight” or “obese” child may be contributing to the problem. Beliefs about what an attractive weight is may be affected by culture.²³ For example, it has been reported that African American girls are more satisfied with heavier bodies than are Caucasian girls.⁵ Likewise, the Hispanic population’s perceptions of weight differed from other groups:

Parents, Hispanic parents especially, call their normal-weight children “skinny” and the kids that go to the 90th percentile and above (in weight) “normal.” Parents must be in agreement that there is a problem with their child’s weight before any real progress in treating the child can occur. (Interview, Nurse Practitioner)

Another concern is patient compliance. Changing the eating habits of children may not be feasible because of the socioeconomic status of the families and the availability of healthy meal options.²⁴ In addition to the increased cost of healthier options, the neighborhood retail food stores may be a contributing factor to the child’s obesity status.^25,26 It has been found that the incidence of overweight, especially in those children initially higher than the 85th percentile in BMI for age, is increased in children from low-income backgrounds, even as young as 3 years of age.^27-29

Changes in eating habits may take the cooperation of the whole family. Practitioners should encourage parents to treat their child’s weight issue as a family concern, helping to educate them about the danger of obesity in childhood. By informing parents about the increased morbidity of cardiovascular illness later in life in those with pediatric obesity,³⁰ they may be motivated to change their own lifestyle and to be more supportive of their child’s weight loss journey.^31-33 Parents can serve as role models to their children, helping to mold their eating and activity behavior from an early age.⁵ Accessibility of wiser food choices is critical and, as stated by a family practitioner during one of the interviews, “Parents need to have healthy snacks available and have a way to encourage and reinforce healthy snacks.” Involving the whole family will also help the child who is at risk or already overweight from feeling singled out. Part of the clinician’s job is to help counsel families to motivate them along the path to a healthier lifestyle. By helping the family to change together, goals can be set, and the child can be recognized for their achievements.

One of the main challenges in suggesting appropriate weight management strategies may lie within the graduate medical education programs of primary care specialists. It has been reported that few pediatricians and family practitioners feel adequately prepared to tackle the growing problem of obesity. Adequate training during residency is lacking, especially education in the counseling required to care for obese children.³⁴ Additionally, there is limited training available in some programs in the prevention of childhood obesity, even with the acknowledgment of obesity’s importance and prevalence in society today.³⁵ This may lead to underdiagnosis and undertreatment of obese children in the primary care setting.³⁶ Luckily, clinicians do seem willing to learn, as echoed by the following insight from one of the medical providers interviewed for this study:

The five-year cure-rate for obesity is zero, which has always stuck with me since my residency. Though I am making progress towards my goals of addressing obesity with my patients, I wish I had done a better job from the start. The whole point is for all of us (pediatricians) to get better at treating it. (Interview, Pediatrician)

Time spent with the patient may also be a factor, as physicians who spend more time with their patients are more likely to discuss healthy weight maintenance.³⁷ With limited time during a patient encounter and poor insurance reimbursement for the treatment of childhood obesity, the demands that are placed on the clinicians are significant.³⁸ In our study, out of 158 patient charts evaluated, 30 (19%) children were not covered by any insurance or were labeled as “self-pay.” 63 (39.9%) children were on Medicaid. There were 66 (41.8%) patients’ charts where the insurance information was left blank or could not be found. There were no children in our study who were covered by private insurance; however, the clinics associated with our study serve predominantly low-income urban families, especially of Hispanic ethnicity. Many of the physicians in our study noted that while endocrinology referrals were indicated, they were seldom given since many families could not afford the referral visit.

Although some interesting findings were revealed when using the Score 1 for Health database and conducting retrospective chart reviews at local clinics in urban Kansas City, there were some limitations in the study design. Data were only collected at two of the five clinics contacted. Subsequently, a small percentage of the patient charts for those who fit the study inclusion criteria were able to be located at these specific clinics and ultimately reviewed. Further, the Score 1 for Health program only serves as a representative group of the greater Kansas City area and is not inclusive of the overall urban population. Most (79%) of the students screened by the Score 1 for Health Program were of non-White ethnicities (Black, Hispanic, Asian, American Indian, and unknown), and 86% of the students qualified for the National School Lunch Program sponsored by the federal government.⁶ It has been shown that minority, low income populations may have increased correlations with obesity.³⁹ The majority of the patient charts that were found for this study came from self-identified Hispanic children (71%). Furthermore, inherent in any retrospective chart review, the data were fully reliant on the accuracy of the physician records.

Conclusion

Because there has been a plateau in the prevalence of high BMI from academic years 2003-2004 to 2005-2006, there is reason to be optimistic about the future of pediatric obesity.⁴⁰ However, many clinicians are still not able to recognize or treat this disease. There is little consistency amongst health care providers in which therapies are most useful, and disagreement continues as to which barriers to treatment are most incumbent to beginning therapy. The responsibility of encouraging every child to live a healthy lifestyle lies with both the clinician and the patient, and more research needs to be done on how clinicians can realistically and successfully incorporate effective management of pediatric obesity in the care of each patient.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

References

Wang

Lobstein

. Worldwide trends in childhood overweight and obesity. Int J Pediatr Obes. 2006;1:11-25.

Han

Lawlor

Kimm

. Childhood obesity. Lancet. 2010;375:1737-1748.

Traveras

. Youths’ perceptions of overweight-related prevention counseling at a primary care visit. Obesity. 2007;15:831-836.

Perrin

Finkle

Benjamin

. Obesity prevention and the primary care pediatrician’s office. Curr Opin Pediatr. 2007;19:354-361.

Barlow

. Expert Committee. Expert committee recommendations regarding the prevention, assessment, and treatment of child and adolescent overweight and obesity: summary report. Pediatrics. 2007;120(suppl 4):S164-S192.

Campbell

Stering

. Score 1 for Health 2008 Community Report. http://pub.kcumb.edu/SC1/PDF/Score1CommRep08.pdf. Accessed February 6, 2013.

Freedman

Sherry

. The validity of BMI as an indicator of body fatness and risk among children. Pediatrics. 2009;124(suppl 1):S23-S34.

Freedman

Patel

Srinivasan

. The contribution of childhood obesity to adult carotid intima-mediated thickness: the Bogalusa Heart Study. Int J Obes. 2008;32:749-756.

Meyer

Kundt

Steiner

Schuff-Werner

Kienast

. Impaired flow-mediated vasodilation, carotid artery intima-media thickening, and elevated endothelial plasma markers in obese children: the impact of cardiovascular risk factors. Pediatrics. 2006;117:1560-1567.

10.

Sinha

Fisch

Teague

. Prevalence of impaired glucose tolerance among children and adolescence with marked obesity. N Engl J Med. 2002;346;802-810.

11.

Wabitsch

Hauner

Hertrampf

. Type II diabetes mellitus and impaired glucose regulation in Caucasian children and adolescents with obesity living in Germany. Int J Obes Relat Metab Disord. 2004;28:307-313.

12.

Kong

Williams

Rhyne

. Acanthosis Nigricans: high prevalence and association with diabetes in a practice-based research network consortium: a PRImary care Multi-Ethnic Network (PRIME Net) study. J Am Board Fam Med. 2010;23:476-485.

13.

Wills

. Orthopedic complications of childhood obesity. Pediatr Phys Ther. 2004;16:230-235.

14.

Murray

Wilson

. Changing incidence of slipped capital femoral epiphysis: a relationship with obesity? J Bone Joint Surg Br. 2008;90:92-94.

15.

Bowen

Assis

Sinha

Hassink

Littleton

. Association among slipped capital femoral epiphysis, tibia vera, and type 2 juvenile diabetes. J Pediatr Orthop. 2009;29:341-344.

16.

Taylor

Theim

Mirch

. Orthopedic complications of overweight in children and adolescents. Pediatrics. 2006;117:2167-2174.

17.

Sánchez-Villegas

Pimenta

Beunza

Guillen-Grima

Toledo

Martinez-Gonzalez

. Childhood and young adult overweight/obesity and incidence of depression in the SUN project. Obesity. 2010;18: 1443-1448.

18.

Dockray

Susman

Dorn

. Depression, cortisol reactivity, and obesity in childhood and adolescence. J Adolesc Health. 2009;45:344-350.

19.

Noal

Menezes

Macedo

Dumith

. Childhood body mass index and risk of asthma in adolescence: a systematic review. Obes Rev. 2011;12:93-104.

20.

Koebnick

Getahun

Smith

Porter

Der-Sarkissian

Jacobsen

. Extreme childhood obesity is associated with increased risk for gastroesophageal reflux disease in a large population-based study. Int J Pediatr Obes. 2011;6:e257-e263.

21.

Kohler

Tormaehlen

Kennedy

. Differences in the association between obesity and obstructive sleep apnea among children and adolescents. J Clin Sleep Med. 2009;5:506-511.

22.

DuBard

Gizlice

. Language spoken and differences in health status, access to care, and receipt of preventive services among US Hispanics. Am J Public Health. 2008;98:2021-2028.

23.

Ceballos

Czyzewska

. Body image in Hispanic/Latino vs. European American adolescents: implications for treatment and prevention of obesity in underserved populations. J Health Care Poor Underserved. 2010;21:823-838.

24.

Gittelsohn

Sharma

. Physical, consumer, and social aspects of measuring the food environment among diverse low-income populations. Am J Prev Med. 2009;36(4 suppl):S161-S165.

25.

Larson

Story

Nelson

C. Neighborhood environments: disparities in access to healthy foods in the US. Am J Prev Med. 2009;36:74-81.

26.

Zick

Smith

Fan

Brown

Yamada

Kowaleski-Jones

. Running to the store? The relationship between neighborhood environments and the risk of obesity. Soc Sci Med. 2009;69:1493-1500.

27.

Robbins

Khan

Lisi

Robbins

Michel

Torcato

. Overweight among young children in the Philadelphia health care centers: Incidence and prevalence. Arch Pediatr Adolesc Med. 2007;161:17-20.

28.

Goodman

Slap

Huang

. The public health impact of socioeconomic status on adolescent depression and obesity. Am J Public Health. 2003;93:1844-1850.

29.

Strauss

Pollack

. Epidemic increase in childhood overweight, 1986-1998. JAMA. 2001;286:2845-2848.

30.

Allcock

Gardner

Sowers

. Relation between childhood obesity and adult cardiovascular risk. Int J Pediatr Endocrinol. 2009;2009:108-187.

31.

Perrin

Finkle

Benjamin

. Obesity prevention and the primary care pediatrician’s office. Curr Opin Pediatr. 2007;19:354-361.

32.

Rhee

De Lago

Arscott-Mills

Mehta

Davis

. Factors associated with parental readiness to make changes for overweight children. Pediatrics. 2005;116:e94-e101.

33.

Van Duyn

McCrae

Wingrove

. Adapting evidence-based strategies to increase physical activity among African Americans, Hispanics, Hmong, and Native Hawaiians: a social marketing approach. Prev Chronic Dis. 2007;4:A102.

34.

Wolff

Rhodes

Ludwig

. Training in childhood obesity management in the United States: a survey of pediatric, internal medicine-pediatrics and family medicine residency program directors. BMC Med Educ. 2010;10:18.

35.

Goff

Holmboe

Curry

. Barriers to obesity training for pediatric residents: a qualitative exploration of residency director perspectives. Teach Learn Med. 2006;18:348-355.

36.

O’Brien

Holubkov

Reis

. Identification, evaluation, and management of obesity in an academic primary care center. Pediatrics. 2004;114:e154-e159.

37.

Rattay

Fulton

Galuska

. Weight counseling patterns of U.S. pediatricians. Obes Res. 2004;12:161-169.

38.

Tershakovec

Watson

Wenner

Marx

. Insurance reimbursement for the treatment of obesity in children. J Pediatr. 1999;134:573-578.

39.

Wang

Zhang

. Are American children and adolescents of low socioeconomic status at increased risk of obesity? Changes in the association between overweight and family income between 1971 and 2002. Am J Clin Nutr. 2006;84:707-716.

40.

Ogden

Carroll

. Prevalence of Obesity Among Children and Adolescents: United States, Trends 1963-1965 Through 2007-2008. Hyattsville, MD: National Center of Health Statistics, Division of Health and Nutrition Examination Surveys; June 2010.