Children Health Issues - Library Research Assignment

j.2047-6310.2013.00154.x.pdf

Home >Education homework help >Children Health Issues - Library Research Assignment

Prevalence of obesity and extreme obesity in children aged 3–5 years J. C. Lo1,2, B. Maring2, M. Chandra1, S. R. Daniels3, A. Sinaiko4, M. F. Daley5, N. E. Sherwood6, E. O. Kharbanda6, E. D. Parker6, K. F. Adams6, R. J. Prineas7, D. J. Magid5, P. J. O'Connor6 and L. C. Greenspan8 1Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA; 2Department of Medicine, Kaiser Permanente Oakland Medical Center, Oakland, CA, USA; 3University of Colorado School of Medicine, Denver, CO, USA; 4Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA; 5Institute for Health Research, Kaiser Permanente Colorado, Denver, CO, USA; 6HealthPartners Institute for Education and Research, Minneapolis, MN, USA; 7Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, USA; 8Department of Pediatrics, Kaiser Permanente San Francisco Medical Center, San Francisco, CA, USA

Received 26 October 2012; revised 20 December 2012; accepted 1 January 2013

What is already known about this subject • The prevalence of obesity in the United States has

increased dramatically over the past three decades. • There is a growing spectrum of severe obesity among

children and adolescents. • Obesity trends and race/ethnic differences may be evident

at a young age.

What this study adds • Among children aged 3–5 years, the prevalence of obesity

and severe obesity was higher in boys than in girls, and highest among children of Hispanic ethnicity.

• Within this young age group, higher body mass index (BMI) was associated with greater height percentile.

• Among obese children aged 5 years, provider recognition of obesity or elevated BMI was high, approaching 80% of children.

Summary Background: Early childhood adiposity may have significant later health effects. This study examines the prevalence and recognition of obesity and severe obesity among preschool-aged children.

Methods: The electronic medical record was used to examine body mass index (BMI), height, sex and race/ethnicity in 42 559 children aged 3–5 years between 2007 and 2010. Normal or underweight (BMI < 85th percentile); overweight (BMI 85th–94th percentile); obesity (BMI � 95th percentile); and severe obesity (BMI � 1.2 ¥ 95th percentile) were classified using the 2000 Centers for Disease Control and Prevention growth charts. Provider recognition of elevated BMI was examined for obese children aged 5 years.

Results: Among 42 559 children, 12.4% of boys and 10.0% of girls had BMI � 95th percentile. The prevalence was highest among Hispanics (18.2% boys, 15.2% girls), followed by blacks (12.4% boys, 12.7% girls). A positive trend existed between increasing BMI category and median height percentile, with obesity rates highest in the highest height quintile. The prevalence of severe obesity was 1.6% overall and somewhat higher for boys compared with girls (1.9 vs. 1.4%, P < 0.01). By race/ethnicity, the highest prevalence of severe obesity was seen in Hispanic boys (3.3%). Among those aged 5 years, 77.9% of obese children had provider diagnosis of obesity or elevated BMI, increasing to 89.0% for the subset with severe obesity.

Conclusions: Obesity and severe obesity are evident as early as age 3–5 years, with race/ethnic trends similar to older children. This study underscores the need for continued recognition and contextualization of early childhood obesity in order to develop effective strategies for early weight management.

Keywords: Children, obesity, preschool, severe obesity.

Address for correspondence: Dr JC Lo, Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA 94612, USA. E-mail: [email protected] © 2013 The Authors Pediatric Obesity © 2013 International Association for the Study of Obesity. Pediatric Obesity 9, 167–175

PEDIATRICOBESITY ORIGINALRESEARCH doi:10.1111/j.2047-6310.2013.00154.x

O R

IG IN

A L

R E

S E

A R

C H

Introduction

The current paediatric obesity epidemic in the United States (1) includes approximately 12 million (17%) children aged 2–19 years (2), with obesity defined as body mass index (BMI) at or above the 95th percen- tile using the year 2000 Centers for Disease Control and Prevention (CDC) BMI-for-age growth charts (3,4). While the prevalence of obesity in children appears to have plateaued in recent years (3–5), it is now roughly triple what it was over three decades ago (6,7). Moreover, there is a growing spectrum of severe obesity, previously classified using a threshold of BMI � 99th percentile (1,8,9) and now using the more recently accepted threshold of BMI � 120% of the 95th BMI percentile (10–12), adjusted for age and sex. Using these definitions, studies in selected paediatric populations have found that the preva- lence of severe obesity in children ranges from 3.8 to 7.7% (8,11–13), with severe obesity beginning as early as the preschool years (8,11,12).

The age at which excess weight gain occurs has important implications for child health and develop- ment (14). The range of normal BMI changes during childhood growth, with values generally lowest during ages 4–6 years (adiposity nadir) followed by an increase (adiposity rebound) and subsequent steady rise into the adolescent years (15–17). Early adiposity rebound is associated with greater adipos- ity in mid-childhood (15,16), which, in turn, has been associated with accelerated growth, advanced bone age, earlier pubertal transition and adult obesity (16,18–25). In older children, both overweight and obesity contribute to an increased risk of metabolic syndrome, type 2 diabetes, hypertension, dyslipidae- mia, non-alcoholic steatohepatitis and obstructive sleep apnoea (1,26). Thus, early recognition of severe obesity is an important step towards prevent- ing long-term adverse health consequences.

There are few epidemiologic studies from large healthcare delivery systems examining obesity rates in preschool-aged children. Recent implementation of sophisticated electronic health information tech- nology provides the unique opportunity to monitor onset and progression of overweight and obesity in large community populations, as well as the future ability to link early anthropometric findings to clinical outcomes. The primary objective of this study was to examine anthropometric findings obtained in clinical practice from a large contemporary cohort of chil- dren aged 3–5 years to (i) determine the prevalence of obesity and severe obesity and differences by race/ethnicity, sex and stature; (ii) compare estimates using BMI percentile, Z-score or percentage above

the 95th BMI percentile as thresholds for extremely high BMI-for-age; (iii) determine whether children with BMI � 95th percentile were recognized by their provider and (iv) to review the anthropometric records of individuals whose measured weight and/or BMI values were flagged by the CDC growth chart programme (27) as being biologically implausi- ble values (28) to determine whether these were actually children with extreme obesity.

Methods Kaiser Permanente Northern California (KPNC) is a large integrated healthcare delivery system providing care to over three million members in Northern Cali- fornia, of whom approximately 6% are children under the age of 6 years. This study examines data derived from 42 620 3- to 5-year-old children from a retro- spective cohort of 160 300 KPNC children aged 3–17 years who had BMI and blood pressure obtained during a well-child visit between 1 January 2007 and 31 December 2010. All children had at least 6 months health plan membership prior to the index visit and received care within three large KPNC sub-regions. The Institutional Review Board at HealthPartners Institute for Education and Research approved the study with ceding of oversight authority by the KPNC Institutional Review Board. A waiver of informed consent was obtained because of the nature of the study.

The electronic medical record was used to obtain information on age, sex, race/ethnicity and meas- ured height and weight, with BMI calculated as weight (kg) divided by height (m) squared. The year 2000, CDC growth charts were used to calculate age- and sex-specific BMI, height and weight per- centiles, and BMI standard deviation (Z) scores using publically available programmes provided by the CDC (27). Both BMI percentile and the BMI percent- age above the 95th BMI percentile were used to categorize higher degrees of obesity, including a threshold of 1.2 times the 95th BMI percentile to define severe obesity. Subsequent outpatient visits and recognition of obesity and/or elevated BMI within the ensuing year were examined using electronic medical record diagnoses (International Classifica- tion of Diseases, Ninth revision codes 278.00 for obesity, 278.02 for overweight, V85.54 for BMI � 95th percentile and V85.53 for BMI 85th– 94th percentile).

We used three primary methods for data validation because of potential errors in height and weight measurements extracted from the electronic medical record. First, we excluded children in whom the

168 | J. C. Lo et al. O

R IG

IN A

L R

E S

E A

R C

height was flagged as a ‘biologically implausible value’ by the CDC programme (28) (n = 30) and chil- dren whose index visit measurement included a height <61 cm (24 in.), weight <4.5 kg (10 lb) or BMI < 10 kg m-2 (n = 3).

Among the remaining 42 587 children with well- child visit data, we examined growth charts for chil- dren flagged with high biologically implausible values for weight and/or BMI (n = 237); and only 14 were found to be erroneous and excluded. Three children with missing BMI percentile because of erroneously high BMI > 150 kg m-2 were also excluded. Finally, we reviewed growth charts for obese children with BMI or height differing by more than 15% or weight by more than 20% per year at a prior or subsequent visit within 2 years (requiring age �2 years) who also had an (A) index BMI � 99th percentile, (B) index BMI � 1.2 times the 95th percentile, (C) index BMI Z-score � 2.5 or (D) index BMI 95th–98th percentile with another BMI < 95th percentile (n = 193) of whom only 11 were erroneous and excluded. Height, weight or BMI values that were part of a pattern of rapid growth or weight gain persisting over two or more measurements were considered valid. If the anthropometric data provided insufficient informa- tion, or if no prior/subsequent measurements were available (n = 35), progress note documentation of obesity and/or elevated BMI was also examined.

In total, 430 growth charts were reviewed by a paediatric endocrinologist (Louise Greenspan MD) with exclusion of 28 children (0.06% of the entire cohort) because of erroneous or inconsistent values. The final study cohort included 42 559 3- to 5-year- old children.

Statistical methods

All analyses were conducted using SAS version 9.1 (SAS Institute, Cary, NC, USA). Differences between subgroups were compared using the chi-squared test for categorical data. The Cochrane–Armitage test was used to examine the trend in proportions across categories. Linear regression techniques were used to examine the relationship between median height percentile and BMI percentile category. A P-value of <0.05 was considered statistically significant.

Results Among the final cohort of 42 559 children, 7934 (18.6%) were 3 years old, 23 351 (54.9%) were 4 years old and 11 274 (26.5%) were 5 years old (Table 1). Half of the cohort (49.0%) was female. The cohort was racially and ethnically diverse, consisting Ta

b le

1 B

M I cl

as si

fic at

io n

am o n g

ch ild

re n

ag ed

3 –5

ye ar

s w

ith a

w el

l- ch

ild vi

si t

d u rin

g 2 0 0 7 –2

0 1 0

B M

I p

e rc

e n ti le

B M

I %

B M

I %

B M

I Z

S c o

<8 5 th

8 5 th

–9 4 th

� 9 5 th

� 9 7 th

� 1 .1

¥ 9 5 th

p e rc

e n ti le

� 1 .2

¥ 9 5 th

p e rc

e n ti le

2 .0

0 –2

.9 9

� 3 .0

B O

Y S

(2 1 ,7

2 0 )

1 5 ,9

4 6

(7 3 .4

% )

3 ,0

7 6

(1 4 .2

% )

2 ,6

9 8

(1 2 .4

% )

1 ,9

8 0

(9 .1

% )

9 2 6

(4 .3

% )

4 0 3

(1 .9

% )

1 ,2

7 6

(5 .9

% )

4 2 8

(2 .0

% )

A g e

in ye

ar s

(n )

3 ye

ar s

(4 ,0

4 2 )

2 ,9

4 5

(7 2 .9

% )

5 7 6

(1 4 .3

% )

5 2 1

(1 2 .9

% )

3 8 4

(9 .5

% )

1 4 1

(3 .5

% )

4 3

(1 .1

% )

2 4 7

(6 .1

% )

8 6

(2 .1

% )

4 ye

ar s

(1 1 ,9

4 7 )

8 ,8

9 8

(7 4 .5

% )

1 ,6

5 0

(1 3 .8

% )

1 ,3

9 9

(1 1 .7

% )

1 ,0

2 3

(8 .6

% )

4 3 4

(3 .6

% )

1 8 7

(1 .6

% )

6 4 1

(5 .4

% )

2 3 4

(2 .0

% )

5 ye

ar s

(5 ,7

3 1 )

4 ,1

0 3

(7 1 .6

% )

8 5 0

(1 4 .8

% )

7 7 8

(1 3 .6

% )

5 7 3

(1 0 .0

% )

3 5 1

(6 .1

% )

1 7 3

(3 .0

% )

3 8 8

(6 .8

% )

1 0 8

(1 .9

% )

G IR

L S

(2 0 ,8

3 9 )

1 5 ,5

7 3

(7 4 .7

% )

3 ,1

8 9

(1 5 .3

% )

2 ,0

7 7

(1 0 .0

% )

1 ,3

3 8

(6 .4

% )

7 0 5

(3 .4

% )

2 8 5

(1 .4

% )

1 ,0

2 1

(4 .9

% )

6 1

(0 .3

% )

A g e

in ye

ar s

(N )

3 ye

ar s

(3 ,8

9 2 )

2 ,8

2 6

(7 2 .6

% )

6 3 0

(1 6 .2

% )

4 3 6

(1 1 .2

% )

3 1 2

(8 .0

% )

1 4 7

(3 .8

% )

3 9

(1 .0

% )

2 2 8

(5 .9

% )

2 6

(0 .7

% )

4 ye

ar s

(1 1 ,4

0 4 )

8 ,6

4 0

(7 5 .8

% )

1 ,7

3 4

(1 5 .2

% )

1 ,0

3 0

(9 .0

% )

6 3 3

(5 .6

% )

3 1 4

(2 .8

% )

1 2 8

(1 .1

% )

4 7 3

(4 .2

% )

2 9

(0 .3

% )

5 ye

ar s

(5 ,5

4 3 )

4 ,1

0 7

(7 4 .1

% )

8 2 5

(1 4 .9

% )

6 1 1

(1 1 .0

% )

3 9 3

(7 .1

% )

2 4 4

(4 .4

% )

1 1 8

(2 .1

% )

3 2 0

(5 .8

% )

6 (0

.1 %

)

B M

I< 8

5 th

p er

ce n til

e, n o

rm al

o r

u n d

er w

ei g

h t;

B M

I 8

5 th

–9 4

th (9

4 .9

) p

er ce

n til

e, o

ve rw

ei g

h t;

B M

I� 9

5 th

p er

ce n til

e, o

b es

ity ;

B M

I� 1

.2 ¥

9 5

th p

er ce

n til

e, se

ve re

o b

es ity

. N

u m

b er

s re

p re

se n t

ro w

p er

ce n ta

g es

. B

M I,

b o

d y

m as

s in

d ex

Obesity in young children | 169

O R

IG IN

A L

R E

S E

A R

C H

of 26.1% white, 5.9% black, 24.4% Hispanic, 21.8% Asian (including Pacific Islanders) and 21.8% of other or unknown race/ethnicity. There were 4775 (11.2%) children who met the criteria for obesity defined by BMI � 95th percentile. Overall and within each of the age stratum, the proportion with BMI � 95th percen- tile was slightly, but significantly greater for boys than for girls (12.4% vs. 10.0% overall, P < 0.05 for all comparisons). The prevalence of obesity was signifi- cantly lower in 4-year-old children (boys, 11.7%; girls, 9.0%) compared with 3-year-old children (boys, 12.9%; girls, 11.2%) and 5-year-old children (boys, 13.6%; girls, 11.0%) (all P < 0.05), possibly reflecting the adiposity nadir. Across racial/ethnic subgroups (Fig. 1), the prevalence of obesity was highest among Hispanics (boys, 18.2%; girls, 15.2%) fol- lowed by blacks (boys, 12.4%; girls, 12.7%, P < 0.05 for within gender comparisons). Asian girls tended to have a lower prevalence (6.9%) compared with white girls (7.9%; P = 0.05), and Asian boys had a higher prevalence (10.9%) compared with white boys

(8.6%; P < 0.001). A total of 7.8% of children had BMI � 97th percentile, with a greater proportion among boys compared with girls (9.1 vs. 6.4%, P < 0.001) and the highest proportions in Hispanic children (13.9% for boys; 10.4% for girls, Fig. 1). Approximately, half (49.2%) of the children with BMI � 97th percentile also had a BMI � 1.1 ¥ 95th percentile. When categorized by BMI Z-score �3.00, only 0.3% of girls were identified compared with 2.0% of boys (P < 0.001), with almost no girls iden- tified by age 5 years (0.1%).

Using BMI-for-age criteria for severe obesity, 1.6% of children had BMI � 1.2 times the 95th BMI per- centile (1.9% for boys and 1.4% for girls, P < 0.001). This prevalence was significantly lower than that ascertained when using a threshold of BMI � 99th percentile (3.9% overall, 5.1% for boys and 2.7% for girls, P < 0.001). For both thresholds, a male pre- dominance was seen. Across racial/ethnic sub- groups, Hispanic boys had the highest prevalence of severe obesity (3.3%, P < 0.01 compared with boys of white, black or Asian race/ethnicity, and compared with Hispanic and black girls). Among girls, Hispanic and black girls had the highest prevalence of severe obesity (2.2 and 1.7%, respectively, P < 0.05 when compared with white and Asian girls; P = 0.30 when comparing Hispanic and black girls).

Figure 2 shows the median height percentile by BMI percentile subgroup for each age by gender. Among children with BMI < 85th percentile, the median height percentile was around the 50th per- centile. However, increasing BMI percentile category was associated with an increase in the median height percentile (significant linear trend, P < 0.001) within each age–sex stratum. Figure 3 shows the increas- ing proportions of children with BMI at or above the 95th and 97th percentiles across increasing height percentile in quintiles, (P < 0.001, test for trend).

Included in this study were 223 children with extreme BMI (n = 156) or both extreme BMI and weight (n = 67) values that were correct despite iden- tification by the CDC-based programme as high ‘bio- logically implausible values’. As shown in Table 2, these included 3.5-fold more boys than girls and the majority were of Hispanic or Asian race/ethnicity. All 223 children had BMI and weight percentile values in the 99th-100th percentile range, BMI Z-score above 2.5, and BMI exceeding 1.2 times the 95th BMI percentile for age and sex (Table 2). Each age–sex group also demonstrated extremely high median height percentiles (>80th percentile). Although 0.9% had Prader–Willi syndrome, most did not demon- strate obesity-related conditions. The most promi- nent comorbidity was asthma, identified in 17.5% of

Figure 1 The proportion of children by sex and race/ ethnicity according to body mass index (BMI) classification (BMI � 95th percentile, obesity; BMI � 1.2 ¥ 95th percen- tile, severe obesity).

170 | J. C. Lo et al. O

R IG

IN A

L R

E S

E A

R C

this subgroup based on coded visit diagnoses in the prior 6 months.

We examined the frequency of overweight and obesity recognition over the ensuing year after the index well-child visit in the 1389 (12.3%) of 11 274 children aged 5 years with BMI � 95th percentile because this age represents the beginning of the BMI trajectory beyond the adiposity nadir. The major- ity (86.9%) had continuous membership for at least 1 year after the well-child visit, with one or more sub- sequent ambulatory visits among 76.5% overall and 80.2% obese children. Among these 1389 children, 71.0% had a visit diagnosis of either obesity or elevated BMI � 95th percentile and an additional 6.9% had a diagnosis relating to overweight (or BMI 85th–94th percentile), all of whom received routine nutrition and/or exercise counselling. There were 573 boys and 393 girls aged 5 years with BMI � 97th percentile in whom recognition of elevated BMI � 95th percentile and/or obesity was docu-

mented in 77.6%. Among the subset of 173 boys and 118 girls with severe obesity (BMI � 1.2 ¥ 95th BMI-for-age percentile), recognition of elevated BMI � 95th percentile and/or obesity was higher at 89.0%.

Discussion In this cohort of more than 40 000 preschool-aged children (3–5 years old), 12.4% of boys and 10.0% of girls met criteria for obesity (BMI � 95th percentile). While fewer children met criteria for severe obesity defined by BMI � 1.2 times the 95th percentile (1.6%), the majority of obese children (69.5%) exceeded the 97th BMI percentile. Across increasing BMI strata, the prevalence was highest among His- panic boys. These findings complement data from other studies demonstrating that the prevalence of high BMI-for-age in older children is greatest among Hispanic boys and black girls (5,8). A study of 2452 younger urban children similarly found that a disparity

Figure 2 Median height percentile by body mass index (BMI) percentile in boys and girls. Significant differences in median height percentile were seen across BMI categories for each age–sex stratum, with a significant linear trend (P < 0.001 within each age–sex category).

Figure 3 Proportion of children with body mass index (BMI) � 95th percentile (BMI 95th–96th percentile or BMI � 97th percentile) by increasing height quintile in boys and girls aged 3–5 years old. P < 0.001 for trend across increasing height category.

Obesity in young children | 171

O R

IG IN

A L

R E

S E

A R

C H

between Hispanic and non-Hispanic children can be identified as early as 3 years of age (29).

This study found that in the context of routine paediatric care, a relatively high percentage of obese 5-year-old children had their obesity recognized by their clinical caregivers, as ascertained from the elec- tronic medical record; it is possible that recognition rates would have been even higher had all clinical encounter notes been systematically reviewed for this study. The proportion of children with subse- quent outpatient visits during the ensuing year was also extremely high, suggesting there are opportuni- ties to initiate preventive measures at this early age.

Both the 99th BMI-for-age percentile threshold and a BMI threshold of 1.2 times the 95th percentile have been used as measures of severe obesity (1,8–12). While the 99th percentile identified a larger propor- tion of children, concerns have been raised about the accuracy of this threshold when using the CDC growth charts, given the lack of fit to empiric data (10). Furthermore, use of BMI percentile for stratifi- cation of extremely high BMI values is limited by contraction of percentile values at the upper bound where large changes in BMI result in minimal change in BMI percentile (30,31). The use of BMI Z-score is also limited by an upper bound, depending on age and sex (31). Almost no girls aged 5 years had a Z-score �3.00, because of the fact that Z-scores beyond 4.00 are undefined for girls and boys over the age of 4 and 6 years, respectively (31). These findings highlight challenges in classification of extremely high BMI-for-age in children, particularly for contemporary populations who represent a right- ward shift from historic populations used for devel- opment of the year 2000 CDC growth charts (17). Classifying high BMI values as a percentage of the 95th percentile has been proposed as a more flexible approach to characterizing obesity severity based on evidence that this approach may provide a better fit to empiric data than BMI percentile estimates above the 97th percentile (10). The currently preferred defi- nition of severe obesity is a BMI �1.2 times the 95th percentile when using the CDC growth charts (10– 12), a threshold that demonstrates better approxi- mation of the empiric 99th BMI percentile (10). Consistent with these recommendations, a new growth chart based on BMI percentage above the 95th percentile has recently been proposed for clini- cal tracking of severely obese children (32). Our study found that using a BMI threshold of �1.2 ¥ 95th percentile identified 1.9% of boys and 1.4% of girls who met criteria for severe obesity. Because the range of BMI values within this young age group is relatively narrow compared with olderTa

b le

2 D

em o g ra

p h ic

an d

an th

ro p

o m

et ric

fin d

in g s

in th

e 2 2 3

ch ild

re n

w ith

va lid

m ea

su re

m en

ts o fw

ei g h t

an d

B M

Id es

p ite

d es

ig n at

io n

as h ig

h ‘b

io lo

g ic

al ly

im p

la u si

b le

va lu

es ’

u si

n g

th e

Ye ar

2 0 0 0

C en

te rs

fo r

D is

ea se

C o n tr

o la

n d

P re

ve n tio

n g ro

w th

ch ar

t re

fe re

n ce

d at

M e d

ia n

(IQ R

) W

e ig

h t

(k g

) M

e d

ia n

(IQ R

) H

e ig

h t

(c m

) M

e d

ia n

(IQ R

) H

e ig

h t

p e rc

e n ti le

M e d

ia n

(IQ R

) B

M I

(k g

m -2

) �

1 .5

¥ 9 5 th

B M

I p

e rc

e n ti le

n (%

)

R a c e /e

th n ic

it y

B o ys

(n =

1 7 3 )

3 1 .5

(2 8 .0

–3 4 .5

) 1 1 1 .1

(1 0 6 .7

–1 1 4 .3

) 8 2 .1

(6 5 .4

–9 2 .1

) 2 5 .1

(2 4 .1

–2 6 .9

) 4 2

(2 4 .3

% )

1 2 .1

% W

h ite

4 .1

% B

la ck

4 3 .9

% H

is p

an ic

2 4 .9

% A

si an

A g e

3 (n

= 2 0 )

2 7 .9

(2 5 .4

–3 0 .3

) 1 0 5 .7

(1 0 1 .6

–1 0 6 .7

) 9 0 .7

(7 8 .1

–9 3 .1

) 2 5 .3

(2 3 .5

–2 7

.0 )

5 (2

5 .0

% )

A g e

4 (n

= 9 3 )

2 9 .7

(2 7 .0

–3 3 .6

) 1 0 8 .5

(1 0 5 .4

–1 1 3 .0

) 8 1 .5

(6 4 .9

–9 3 .1

) 2 4 .6

(2 3 .8

–2 6

.9 )

2 4

(2 5 .8

% )

A g e

5 (n

= 6 0 )

3 4 .0

(3 2 .3

–3 7 .7

) 1 1 4 .9

(1 1 3 .0

-1 1 7 .8

) 8 0 .3

(6 8 .9

–8 8 .5

) 2 5 .5

(2 4 .8

–2 6

.7 )

1 3

(2 1 .7

% )

G irl

s (n

= 5 0 )

3 2 .1

(2 8 .6

–3 5 .5

) 1 0 8 .6

(1 0 4 .8

–1 1 4 .3

) 8 4 .9

(7 1 .0

–9 1 .8

) 2 6 .5

(2 5 .7

–2 7

.7 )

1 4

(2 8 .0

% )

6 .0

% W

h ite

6 .0

% B

la ck

6 0 .0

% H

is p

an ic

1 4 .0

% A

si an

A g e

3 (n

= 1 3 )

2 7 .7

(2 6 .2

–2 8 .8

) 1 0 3 .5

(1 0 0 .3

–1 0 5 .4

) 9 1 .4

(6 0 .3

–9 1 .8

) 2 5 .7

(2 5 .2

–2 6

.4 )

3 (2

3 .1

% )

A g e

4 (n

= 2 0 )

3 1 .1

(2 8 .7

–3 3 .0

) 1 0 6 .6

(1 0 5 .4

–1 1 2 .4

) 8 2 .6

(7 3 .4

–9 5 .1

) 2 6 .4

(2 5 .4

–2 7

.2 )

5 (2

5 .0

% )

A g e

5 (n

= 1 7 )

3 5 .6

(3 4 .8

–3 8 .7

) 1 1 4 .3

(1 1 3 .0

–1 1 8 .1

) 8 5 .1

(7 4 .5

–9 0 .1

) 2 7 .5

(2 6 .6

–2 8

.6 )

6 (3

5 .3

% )

*A ll

ch ild

re n

h ad

B M

I an

d w

ei g

h t

va lu

es in

th e

9 9

th -1

0 0

th p

er ce

n til

e ra

n g

e an

d a

B M

I va

lu e

� 1

.2 ¥

9 5

th B

M I p

er ce

n til

e. P

er ce

n ta

g e

n u m

b er

s re

p re

se n t

ro w

p er

ce n ta

g es

. B

M I,

b o

d y

m as

s in

d ex

; IQ

R ,

in te

rq u ar

til e

ra n g

172 | J. C. Lo et al. O

R IG

IN A

L R

E S

E A

R C

children where the growth curves widen consider- ably, use of lower thresholds such as the 97th per- centile or 1.1 ¥ 95th percentile may also be helpful in targeting young obese children at risk for progression to more severe degrees of obesity.

Most children initially flagged as having biologically implausible high values for BMI and/or weight had, in fact, valid measurements of these indices. More than three quarters were boys, of whom a large propor- tion were Hispanic (44%) or Asian (25%). The CDC programme uses fixed exclusion ranges provided by the World Health Organization to define ‘biologically implausible values’ with the goal of removing these excessively high values that may be due to entry errors or mis-measurement (27,28). However, our findings demonstrate that values labelled as implau- sible should not be automatically excluded in young children without more careful evaluation of growth trajectory. Other investigators have used algorithms based on incremental weight or height values below the first or above the 99th percentiles to identify potential errors in the electronic medical record (33); using those methods, our study identified no addi- tional children for exclusion. In this study, we used data from prior and/or subsequent clinical visits, where inconsistencies in measured height, weight and BMI within specific subgroups were used to determine the need for individual growth chart review.

Level of BMI was directly associated with height percentile, consistent with the known interrelation- ship of BMI and linear growth; heavier children were taller and those in the highest BMI category had the tallest stature. The increasing proportion of children with BMI � 95th percentile or �97th percentile across increasing height quintiles is consistent with data from others who observed a more than 10-fold increase in obesity prevalence across lowest to highest height quintile for children 3–10 years of age (34). This early association between BMI and growth may have important implications for subsequent pubertal development, final adult height and adult adiposity. One of the challenges associated with assessment of adiposity status during the early years of growth is that changes in BMI represent both changes in adiposity and changes in lean mass. However, calculated BMI is strongly correlated with percent body fat measured by dual energy X-ray absorptiometry (35); and differences in BMI at a given height are associated with differences in body fatness. Additional demographic variation in the rela- tionship of BMI to body fat may also be relevant when comparing BMI-for-age across different popu- lation subgroups (36).

It is not clear whether obesity at this early age is related to differences in behaviours and feeding pat- terns, e.g., breast milk vs. formula and the timing of introduction of solid foods, particularly in a racially and ethnically diverse cohort. Parental obesity, maternal conditions, environment and behaviour are also known to modulate the risk of childhood obesity (37,38), but these contextual factors could not be ascertained in this study because of the limitations of the electronic medical record. Although this study did not include children under the age of 3, obesity trends may begin as early as infancy where exami- nation of weight-for-length has been used to esti- mate the prevalence of infant obesity (39).

In summary, the high prevalence of early onset obesity is of great concern from a public health per- spective, because of the strong tracking effect of childhood obesity and relation of childhood obesity to adult metabolic complications and other clinical comorbidities. This concern is underscored by the finding that extreme obesity is significantly higher in specific ethnic groups and, in particular, Hispanics. While future research is needed to track the long- term outcomes among these children, the early rec- ognition of obesity by healthcare providers and the high proportion with follow-up care within this young age group may provide an important framework to support delivery of effective and timely interventions for obesity management and prevention at an early age.

Conflicts of interest statement No conflict of interest was declared.

Acknowledgements JL, BM, MC, SD, AS and LG conceived the project. MC conducted the data analyses. JL, BM and LG drafted the initial manuscript. All authors provided critical input on data analysis and interpretation, revised the manuscript for important intellectual content and approved the final version. The authors would like to acknowledge Joel Gonzalez for his support with manuscript preparation. This study was funded by the National Heart, Lung and Blood Insti- tute at the National Institutes of Health 1RO1HL093345 to HealthPartners Research Foun- dation (Patrick O'Connor, Principal Investigator) and conducted within the Cardiovascular Research Network, a consortium of research organizations affiliated with the HMO Research Network and spon- sored by the National Heart Lung and Blood Institute (U19 HL91179-01).

Obesity in young children | 173

O R

IG IN

A L

R E

S E

A R

C H

References

1. 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–S192. 2. Ogden CL, Lamb MM, Carroll MD, Flegal KM. Obesity and socioeconomic status in children and adolescents: United States, 2005–2008. NCHS Data Brief 2010; 51: 1–8. 3. Ogden CL, Carroll MD, Curtin LR, Lamb MM, Flegal KM. Prevalence of high body mass index in US children and adolescents, 2007–2008. JAMA 2010; 303: 242–249. 4. Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of obesity and trends in body mass index among US children and adolescents, 1999–2010. JAMA 2012; 307: 483–490. 5. Ogden CL, Carroll MD, Flegal KM. High body mass index for age among US children and adolescents, 2003– 2006. JAMA 2008; 299: 2401–2405. 6. Hedley AA, Ogden CL, Johnson CL, Carroll MD, Curtin LR, Flegal KM. Prevalence of overweight and obesity among US children, adolescents, and adults, 1999–2002. JAMA 2004; 291: 2847–2850. 7. Ogden CL, Carroll MD. Prevalence of Obesity Among Children and Adoloescents: United States, Trends 1963– 1965 Through 2007–2008. NCHS Health E-Stat 2010; June: 1–5. 8. Skelton JA, Cook SR, Auinger P, Klein JD, Barlow SE. Prevalence and trends of severe obesity among US chil- dren and adolescents. Acad Pediatr 2009; 9: 322–329. 9. Freedman DS, Mei Z, Srinivasan SR, Berenson GS, Dietz WH. Cardiovascular risk factors and excess adiposity among overweight children and adolescents: the Bogalusa Heart Study. J Pediatr 2007; 150: 12–17. 10. Flegal KM, Wei R, Ogden CL, Freedman DS, Johnson CL, Curtin LR. Characterizing extreme values of body mass index-for-age by using the 2000 Centers for Disease Control and Prevention growth charts. Am J Clin Nutr 2009; 90: 1314–1320. 11. Koebnick C, Smith N, Coleman KJ, et al. Prevalence of extreme obesity in a multiethnic cohort of children and adolescents. J Pediatr 2010; 157: 26–31 e2. 12. Wang YC, Gortmaker SL, Taveras EM. Trends and racial/ethnic disparities in severe obesity among US chil- dren and adolescents, 1976–2006. Int J Pediatr Obes 2011; 6: 12–20. 13. Benson L, Baer HJ, Kaelber DC. Trends in the diag- nosis of overweight and obesity in children and adoles- cents: 1999–2007. Pediatrics 2009; 123: e153–e158. 14. Dietz WH. Critical periods in childhood for the devel- opment of obesity. Am J Clin Nutr 1994; 59: 955–959. 15. Rolland-Cachera MF, Deheeger M, Bellisle F, Sempe M, Guilloud-Bataille M, Patois E. Adiposity rebound in chil- dren: a simple indicator for predicting obesity. Am J Clin Nutr 1984; 39: 129–135. 16. Rolland-Cachera MF, Deheeger M, Maillot M, Bellisle F. Early adiposity rebound: causes and consequences for obesity in children and adults. Int J Obes (Lond) 2006; 30(Suppl. 4): S11–S17.

17. Kuczmarski RJ, Ogden CL, Guo SS, et al. 2000 CDC Growth Charts for the United States: methods and devel- opment. Vital Health Stat 11 2002; 246: 1–190. 18. Demerath EW, Jones LL, Hawley NL, et al. Rapid infant weight gain and advanced skeletal maturation in childhood. J Pediatr 2009; 155: 355–361. 19. Forbes GB. Nutrition and growth. J Pediatr 1977; 91: 40–42. 20. Mamun AA, Hayatbakhsh MR, O’Callaghan M, Wil- liams G, Najman J. Early overweight and pubertal matura- tion – pathways of association with young adults’ overweight: a longitudinal study. Int J Obes 2009; 33: 14–20. 21. Must A, Naumova EN, Phillips SM, Blum M, Dawson- Hughes B, Rand WM. Childhood overweight and matura- tional timing in the development of adult overweight and fatness: the Newton Girls Study and its follow-up. Pediat- rics 2005; 116: 620–627. 22. Sandhu J, Ben-Shlomo Y, Cole TJ, Holly J, Davey Smith G. The impact of childhood body mass index on timing of puberty, adult stature and obesity: a follow-up study based on adolescent anthropometry recorded at Christ's Hospital (1936–1964). Int J Obes 2006; 30: 14–22. 23. Freedman DS, Khan LK, Serdula MK, Dietz WH, Srini- vasan SR, Berenson GS. The relation of menarcheal age to obesity in childhood and adulthood: the Bogalusa heart study. BMC Pediatr 2003; 3: 3. 24. Whitaker RC, Pepe MS, Wright JA, Seidel KD, Dietz WH. Early adiposity rebound and the risk of adult obesity. Pediatrics 1998; 101: E5. 25. Williams SM, Goulding A. Early adiposity rebound is an important predictor of later obesity. Obesity (Silver Spring) 2009; 17: 1310. 26. Daniels SR, Jacobson MS, McCrindle BW, Eckel RH, Sanner BM. American Heart Association Childhood Obesity Research Summit: executive summary. Circulation 2009; 119: 2114–2123. 27. A SAS program for the CDC growth charts. [WWW document]. URL http://www.cdc.gov/nccdphp/dnpao/ growthcharts/resources/sas.htm (accessed October 2011). 28. Cut-offs to define outliers in the 2000 CDC Growth Charts. [WWW document]. URL http://www.cdc.gov/ nccdphp/dnpa/growthcharts/resources/BIV-cutoffs.pdf (accessed April 2012). 29. Whitaker RC, Orzol SM. Obesity among US urban preschool children: relationships to race, ethnicity, and socioeconomic status. Arch Pediatr Adolesc Med 2006; 160: 578–584. 30. Cole TJ, Faith MS, Pietrobelli A, Heo M. What is the best measure of adiposity change in growing children: BMI, BMI %, BMI Z-score or BMI centile? Eur J Clin Nutr 2005; 59: 419–425. 31. Woo JG. Using body mass index Z-score among severely obese adolescents: a cautionary note. Int J Pediatr Obes 2009; 4: 405–410. 32. Gulati AK, Kaplan DW, Daniels SR. Clinical tracking of severely obese children: a new growth chart. Pediatrics 2012; 130: 1136–1140.

174 | J. C. Lo et al. O

R IG

IN A

L R

E S

E A

R C

33. Smith N, Coleman KJ, Lawrence JM, et al. Body weight and height data in electronic medical records of children. Int J Pediatr Obes 2010; 5: 237–242. 34. Freedman DS, Khan LK, Serdula MK, Dietz WH, Srinivasan SR, Berenson GS. Inter-relationships among childhood BMI, childhood height, and adult obesity: the Bogalusa Heart Study. Int J Obes Relat Metab Disord 2004; 28: 10–16. 35. Lindsay RS, Hanson RL, Roumain J, Ravussin E, Knowler WC, Tataranni PA. Body mass index as a measure of adiposity in children and adolescents: relationship to adiposity by dual energy x-ray absorptiometry and to car- diovascular risk factors. J Clin Endocrinol Metab 2001; 86: 4061–4067.

36. Daniels SR, Khoury PR, Morrison JA. The utility of body mass index as a measure of body fatness in children and adolescents: differences by race and gender. Pediat- rics 1997; 99: 804–807. 37. Reilly JJ, Armstrong J, Dorosty AR, et al. Early life risk factors for obesity in childhood: cohort study. BMJ 2005; 330: 1357. 38. Salsberry PJ, Reagan PB. Dynamics of early child- hood overweight. Pediatrics 2005; 116: 1329–1338. 39. McCormick DP, Sarpong K, Jordan L, Ray LA, Jain S. Infant obesity: are we ready to make this diagnosis? J Pediatr 2010; 157: 15–19.

Obesity in young children | 175

O R

IG IN

A L

R E

S E

A R

C H