CHILDREN AT RISK
Associations Between Obesity and Comorbid Mental Health,
Developmental, and Physical Health Conditions in a Nationally
Representative Sample of US Children Aged 10 to 17
Neal Halfon, MD, MPH; Kandyce Larson, PhD; Wendy Slusser, MD, MS
From the UCLA Center for Healthier Children, Families, and Communities (Drs Halfon, Larson, and Slusser), Department of Pediatrics, David
Geffen School of Medicine, UCLA (Drs Halfon, Larson, and Slusser), Department of Health Services, School of Public Health, UCLA
(Dr Halfon), Department of Public Policy, School of Public Affairs, UCLA (Dr Halfon), and Department of Community Health Sciences, School
of Public Health, UCLA (Dr Slusser), Los Angeles, Calif
Address correspondence to Neal Halfon, MD, MPH, UCLA Center for Healthier Children, Families, and Communities, 10990 Wilshire,
Ste 900, Los Angeles, CA 90024 (e-mail: nhalfon@ucla.edu).
Received for publication June 25, 2011; accepted October 28, 2012.
ABSTRACT
OBJECTIVE: This large population-based study of US children
considered the association of obesity with a broad range of comorbidities.
This study examined relationships between weight
status and health for US children.
METHODS: We performed cross-sectional analysis of data on
43,297 children aged 10 to 17 from the 2007 National Survey
of Children’s Health. Weight status was calculated from parent
report of child height and weight. Logistic regression models assessed
associations between weight status and 21 indicators of
general health, psychosocial functioning, and specific health
disorders, adjusting for sociodemographic factors.
RESULTS: Using body mass index (BMI) percentiles for age
and sex, 15% of US children were considered overweight
(BMI 85th to <95th percentile), and 16% were obese
(BMI $95th percentile). Compared with children classified as
not overweight, obese children were more likely to have reported
good/fair/poor health (adjusted odds ratio [AOR] 2.18,
95% confidence interval [CI] 1.76–2.69), activity restrictions
(AOR 1.39, 95% CI 1.10–1.75), internalizing problems
(AOR 1.59, 95% CI 1.04–2.45), externalizing problems (AOR
1.33, 95% CI 1.07–1.65), grade repetition (AOR 1.57, 95% CI
1.24–1.99), school problems, and missed school days. Attention
deficit/hyperactivity disorder, conduct disorder, depression,
learning disability, developmental delay, bone/joint/muscle
problems, asthma, allergies, headaches, and ear infections
were all more common in obese children.
CONCLUSIONS: Obese children have increased odds of worse
reported general health, psychosocial functioning, and specific
health disorders. Physicians, parents, and teachers should be
informed of the specific comorbidities associated with childhood
obesity to target interventions that could enhance wellbeing.
Future research should examine additional comorbidities
and seek to confirm associations using longitudinal data and
clinical measures of height and weight.
KEYWORDS: behavior problems; children; chronic health
conditions; comorbidity; obesity
ACADEMIC PEDIATRICS 2013;13:6–13
WHAT’S NEW
This large population-based study of US children examined
the association of obesity with a broad range of
potential comorbidities. Associations were found
between obesity and 19 indicators of general health,
psychosocial functioning, and chronic health condi-
tions.
CHILDHOOD OBESITY HAS dramatically increased over
the last 2 decades.1–3
Studies measuring the impact of the
epidemic also warn of powerful long-term effects on adult
morbidity and mortality, as well as health care costs.4–6
The enduring consequences of childhood obesity not
only include a growing number of obese adults, but also
remarkable increases in comorbid conditions, including
type 2 diabetes, heart disease, hypertension, and various
mental health problems.7
With a focus on childhood
obesity’s future consequences, there has been less attention
paid to the nature, prevalence, and distribution of obesityrelated
comorbidities during childhood.
Unraveling the relationship of childhood obesity to other
comorbid conditions is important for understanding the full
impact of obesity in childhood. Although there is evidence
that growing rates of childhood obesity relate to changes in
caloric intake and caloric expenditure, as a result of a host
of social trends and environmental changes, there are many
other factors that may be contributing to increasing rates of
obesity. Changes in exposures to chemical obesogens,
higher levels of toxic stress, and obesity’s relationship to
the development of neuroregulatory processes associated
with appetite, self-regulation, and impulse control are
just some of the other causal pathways that have been
considered.8–10
A better understanding of the association
of obesity with other health and psychosocial conditions
in childhood may provide important information about
ACADEMIC PEDIATRICS Volume 13, Number 1
Copyright ª 2013 by Academic Pediatric Association 6 January–February 2013
developmental influences and causal pathways of obesity,
as well as provide avenues for more effective primary,
secondary, and tertiary prevention strategies.11,12
Prior studies have identified associations between
obesity in childhood and adolescence and a broad range of
health indicators and comorbidities, including general
health status, health-related quality of life,13–16
specific
health conditions such as attention deficit/hyperactivity
disorder (ADHD) and behavior problems,17–21
asthma and
respiratory infection,22–24
orthopedic problems,25
head-
aches,26,27
and ear infections.28
However, the vast majority
of these studies havebeen based onsmall clinicalor regional
samples, which may not be representative of the general
population of children. They also suffer from small sample
sizes, whichlimitconsiderations of other sociodemographic
confounders. Furthermore, most studies have examined
associations one condition at a time instead of presenting
a comprehensive profile of abroad range of healthindicators
that might be associated with childhood obesity.
The 2007 National Survey of Children’s Health (NSCH)
provides a unique opportunity to examine a comprehensive
set of comorbidities of obesity with new data from a telephone
survey of parents that is representative of the US
population of children. We chose comorbid conditions
on the basis of prior studies that suggested possible associations
with obesity.13–29
We examined the relationships
between weight status and a broad set of mental health,
developmental, and physical health comorbidities while
controlling for other measures of social and economic
status. We also examined whether the relationship between
weight status and comorbid conditions vary for children
from different socioeconomic and racial/ethnic groups.
METHODS
SAMPLE
The 2007 NSCH was conducted by the National Center
for Health Statistics as a module of the State and Local
Area Integrated Telephone Survey. The NSCH used a stratified
random-digit-dial sampling design to achieve a nationally
representative sample of 91,642 parents of children
0 to 17 years of age. One child was randomly selected
from each household, and a detailed telephone interview
was conducted with the parent or guardian who knew the
most about the child’s health and health care. Interviews
of approximately 30 minutes were conducted in English
and Spanish. The interview completion rate, measuring
the proportion of age-eligible households that at least
partially completed interviews among known households
with children under 18 years of age, was 66.0%.
Because parent report of height and weight has been
shown to overestimate overweight among young children,
a finding based on population studies comparing obesity
rates in different national data sets, NSCH only reports
body mass index (BMI) for children in the age range of
10 to 17 years.30
There were a total of 45,897 children in
this age range, and 44,101 had valid data on reported height
and weight. The final study sample was further restricted to
exclude 804 individuals with missing data on any of the
study covariates (N ¼ 43,297) except household income,
which was multiply imputed by NSCH statisticians.31
A comparison of complete cases versus those with missing
data revealed a higher tendency of nonresponse among
black and Hispanic individuals and those with lower household
income and education. There is a small amount of
variability in sample size for each different comorbid
health condition as a result of missing data on the condition
(ranging from n ¼ 43,297 to n ¼ 41,976).
To produce population-based estimates, data records for
each interview were assigned a sampling weight. NSCH
weights were designed to minimize bias by incorporating
adjustments for various forms of survey nonresponse
including poststratification so the sample matches population
control totals on key demographic variables obtained
from the American Community Survey. Further details
on the design and operation of NSCH are reported else-
where.31
This study was exempt from the UCLA institutional
review board.
MEASURES
WEIGHT STATUS
Weight status of children was determined from calculations
of BMI derived from parent-reported child height and
weight. National Center for Health Statistics researchers
categorized children as overweight if their BMI was in
the 85th to <95th percentile compared with children of
the same age and sex, and obese if their BMI was in the
95th percentile and above (continuous height and weight
data were not available for public use). Percentiles were
determined by Centers for Disease Control and Prevention
growth charts.31
COMORBID HEALTH CONDITIONS
General health status indicators include parent-reported
global child health status (dichotomized as excellent/very
good vs good/fair/poor, following previous research)32–35
and presence of an activity limitation, indicated by parent
report of whether the child was “limited or prevented in
any way in his/her ability to do things most children of
the same age can do.” Internalizing and externalizing
problems were measured with selected items from
the Behavior Problems Index.36
Parents report how often
(0 ¼ never, 1 ¼ rarely, 2 ¼ sometimes, 3 ¼ usually, 4 ¼
always) the child feels worthless/inferior, is sad/depressed,
is withdrawn (internalizing), argues too much, bullies or is
cruel, is disobedient, and is stubborn/irritable (externalizing).
Items were summed to create internalizing (range
0–12) and externalizing (0–16) scales. Scores above 6 on
the internalizing scale and above 8 on the externalizing
scale (corresponding with an answer of “sometimes” on
each item) were used to classify problematic behavior.
School functioning was assessed by parent report of
a contact in the past year by the school about problems,
if the child had ever repeated a grade, and number of school
days missed as a result of illness (0–2, 3 or more).
A series of specific health conditions were assessed by
parent report of whether a health care provider had ever
ACADEMIC PEDIATRICS OBESITY AND COMORBIDITY 7
told them that the child had a “condition,” and if so, if the
child currently has the condition. An answer of yes to both
questions identified children with the following mental
health and developmental conditions: ADHD, conduct
disorder, depression, anxiety, learning disability, and
developmental delay. For physical health conditions,
parents reported on children’s dental health (excellent/
very good vs good/fair/poor); whether the child currently
had diabetes, bone/joint/muscle problems, and asthma;
and whether a health care provider told them in the past
year that their child had allergies (hay fever/respiratory,
food/digestive, or eczema/skin), severe headaches, and
ear infections. Number of specific comorbid health conditions
was dichotomized as 0–2 and 3 or more.
ANALYSIS
All statistical analyses were performed by STATA software,
version 11.0 (StataCorp, College Station, Tex).
Survey estimation procedures were applied, and the
Taylor-series linearization method adjusted the standard
errors for the complex survey design. Chi-square tests assessed
differences in comorbidity prevalence by weight
status. Logistic regression models added controls for household
income (below 100% federal poverty level [FPL],
100%–199% FPL, 200%–299% FPL, 300%–399% FPL,
400% FPL or greater), family structure (2 parents, single
mother, other caretakers/single fathers), race/ethnicity
(non-Hispanic white, non-Hispanic black, Hispanic, multiracial/other),
highest parent education, child age in years,
and child gender. These covariates were selected to determine
possible confounding by major social and economic
characteristics and match those used in the previous studies
of obesity comorbidity.13,14,16,20
Results are reported as
odds ratios, which may overestimate relative risk, given
the high prevalence (>10%) of many conditions. For
school functioning outcomes (grade repetition and school
problems), separate analyses also added controls for
number of specific comorbid health conditions, which
includes all mental health, developmental, and physical
health conditions. For ADHD, separate regression models
were run to exclude those taking stimulant medication,
which might be expected to affect associations between
weight status and ADHD. To determine whether
associations between weight status and comorbid health
conditions varied by sociodemographic factors, we tested
statistical interactions between weight and household
income, education, race/ethnicity, age in years, and
gender in separate regression models including controls
for confounders. Adjusted Wald tests assessed the
statistical significance of interactions.
RESULTS
PREVALENCE OF OVERWEIGHT AND OBESITY
The estimated prevalence of overweight based on
parent-reported height and weight for all children aged
10 to 17 was 15% (95% confidence interval [CI] 14–16),
and prevalence of obesity was 16% (95% CI 15–17).
Wide social differentials in rates of overweight and obesity
are apparent (Table 1). Obesity rates were nearly 3 times
higher for children in poor families versus those at 400%
FPL or greater (27% vs 10%), and nearly 2 times higher
for black and Hispanic children versus white nonHispanic
children. Single-mother families, households
with lower education, younger children, and boys also
had elevated childhood obesity rates.
COMORBID HEALTH CONDITIONS BY WEIGHT STATUS
The prevalence of other health problems varied by
weight status for 19 indicators (Table 2). Obese children
had particularly high rates of other health problems. For
example, 11% of obese children had an activity restriction
compared with 7% classified as not overweight, 20%
versus 10% repeated a grade, and 15% versus 9% had
externalizing problems. Common health conditions associated
with obesity include ADHD (12% of obese children vs
8% of those classified as not overweight), learning
disability (15% vs 8%), good/fair/poor teeth (39% vs
27%), asthma (15% vs 9%), allergies (30% vs 26%), and
headaches (9% vs 6%). Overall, obese children had nearly
twice the risk of having 3 or more reported comorbid
mental health, developmental, or physical health conditions
(18% vs 10%), and overweight children had 1.3 times
higher risk (13% vs 10%).
ADJUSTED AND UNADJUSTED ODDS OF HEALTH PROBLEMS
BY WEIGHT STATUS
For 18 indicators, associations between weight status
and health remained significant in logistic regression
models with controls for sociodemographic factors
(Table 3). Most significant differences occurred for children
classified as obese versus not overweight, although
overweight children had modestly elevated health complications
across 5 indicators in adjusted models. Compared
with children classified as not overweight, obese children
were more likely to have good/fair/poor health (adjusted
odds ratio [AOR] 2.18, 95% CI 1.76–2.69), activity restrictions
(AOR 1.39, 95% CI 1.10–1.75), internalizing problems
(AOR 1.59, 95% CI 1.04–2.45), externalizing
problems (AOR 1.33, 95% CI 1.07–1.65), grade repetition
(AOR 1.57, 95% CI 1.24–1.99), school problems, and more
missed school days. Specific health conditions reported as
more common for obese children included the following:
ADHD, conduct disorder, depression, learning disability,
developmental delay, asthma, bone/joint muscle problems,
allergies, headaches, and ear infections. To determine
whether associations between obesity and school functioning
were explained by comorbid conditions, separate
analyses included controls for the number of specific health
conditions. Obesity was still associated with grade repetition
(AOR 1.39, 95% CI 1.09–1.78) but not school problems
(AOR 1.15, 95% CI 0.97–1.37).
A comparison of the adjusted and unadjusted odds ratios
in Table 3 shows considerable attenuation in the magnitude
of the associations between weight status and health
after adjustment for sociosociodemographic factors. For
example, there was a 57% reduction in the odds of conduct
disorder for obese versus not overweight children. Despite
8 HALFON ET AL ACADEMIC PEDIATRICS
attenuation, AORs greater than 1.5 (obese vs not overweight)
were noted for learning disability, developmental
delay, asthma, bone/joint/muscle problems, headaches,
and ear infections.
To determine whether associations between weight
status and ADHD varied by use of stimulant medication,
we estimated separate regression models. Obesity showed
strong associations with ADHD for children not taking
stimulant medication (vs not overweight: odds ratio 1.93,
95% CI 1.26–2.94; AOR 1.85, 95% CI 1.18–2.92), but
there were no associations for children taking stimulant
medication.
Because of concerns that associations between obesity
and comorbid conditions could result from uncontrolled
confounding, we chose 2 conditions with no prior evidence
or existing rationale indicating an association with obesity.
This analysis showed no association between obesity and
minor vision problems and brain injury.
STATISTICAL INTERACTIONS BETWEEN WEIGHT STATUS AND
SOCIODEMOGRAPHIC FACTORS
There were few significant statistical interactions
between childhood weight status and sociodemographic
factors. For diabetes, there was a strong age-associated
interaction. Coefficients from the interaction model
showed that obesity predicted diabetes only for children
beginning at age 15 (AOR 2.23, 95% CI 1.15–4.30), with
odds increasing through age 17. Interactions between
weight status and ethnicity were significant for global
child health status and activity restriction (adjusted Wald
P <.05). Tests of specific interaction coefficients revealed
stronger obesity–health associations for white than for
Hispanic children (P < .05). The magnitude of the obesity
coefficient was smaller for Hispanic children (global child
health AOR 1.62, 95% CI 1.02–2.58; activity restriction
AOR 0.78, 95% CI 0.41–1.48) than white children (global
child health AOR 3.00, 95% CI 2.23–4.06; activity restriction
AOR 1.78, 95% CI 1.33–2.37). Similar trends were
found for global health status and school illness days by
family income: obesity showed stronger associations
with health for higher-income children. There were no
significant interactions between weight status and gender.
DISCUSSION
Overweight and obesity were associated with poorer
health status, lower emotional functioning, and schoolrelated
problems. Greater weight was also associated
with higher rates of specific comorbid conditions,
including ADHD, conduct disorders, depression, learning
disabilities, developmental delay, good/fair/poor teeth,
bone/joint/muscle problems, asthma, allergies, headaches,
and ear infections. Although controlling for social status
dampened the magnitude of these associations, most persisted.
There was also a strong dose–response effect, with
higher weight being associated with a higher prevalence
of comorbid conditions and with greater numbers of comorbidities.
Overweight children had somewhat elevated
Table 1. Childhood Weight Status by Sociodemographic Factors for US Children Aged 10 to 17 From the 2007 National Survey of Children’s
Health*
Characteristic
Unweighted Sample
Size (N)
Not Overweight %
(95% CI)
Overweight %
(95% CI)
Obese %
(95% CI) c2
P
Total 43,297 68 (67–70) 15 (14–16) 16 (15–17)
Household income <.001
<100% FPL 4,229 55 (51–58) 18 (15–21) 27 (25–30)
100%–199% FPL 6,831 62 (59–65) 17 (15–19) 22 (19–24)
200%–299% FPL 7,909 69 (66–71) 15 (13–17) 16 (14–18)
300%–399% FPL 6,965 71 (68–74) 17 (14–20) 12 (10–14)
400% FPL or greater 17,363 78 (76–79) 12 (11–14) 10 (9–12)
Family structure <.001
Two biological/adoptive parents 32,492 71 (69–72) 15 (14–16) 14 (13–16)
Single mother 7,564 61 (58–64) 17 (15–19) 22 (20–24)
Other 3,241 65 (62–69) 15 (13–18) 19 (17–22)
Race/ethnicity <.001
White, non-Hispanic 31,000 73 (72–74) 14 (13–15) 13 (12–14)
Black, non-Hispanic 4,448 59 (56–62) 17 (15–20) 24 (22–26)
Hispanic 4,312 59 (55–63) 18 (14–21) 23 (20–27)
Multiracial/other 3,537 71 (67–75) 15 (13–19) 13 (10–16)
Highest parent education <.001
HS or less 10,071 60 (57–62) 17 (15–19) 23 (21–25)
More than HS 33,226 73 (71–74) 14 (13–15) 13 (12–14)
Child age <.001
10–11 y 8,813 60 (58–63) 17 (15–19) 23 (21–25)
12–13 y 10,046 66 (63–68) 17 (15–19) 17 (15–19)
14–15 y 11,391 73 (71–75) 14 (12–15) 14 (12–15)
16–17 y 13,047 74 (71–76) 13 (11–15) 13 (11–15)
Child gender <.001
Male 22,596 66 (64–67) 15 (14–16) 19 (18–21)
Female 20,701 71 (70–73) 15 (14–17) 14 (12–15)
CI ¼ confidence interval; FPL ¼ federal poverty level; HS ¼ high school.
*Percentages are weighted to be nationally representative.
ACADEMIC PEDIATRICS OBESITY AND COMORBIDITY 9
prevalence of having 3 or more reported comorbid conditions
compared with those not overweight (13% vs 10%),
and obese children were nearly 2 times more likely to
have multiple reported comorbidities (18% vs 10%).
The cross-sectional nature of the data limits our ability
to determine whether obesity is causing the comorbid
condition (ie, a complication), whether the comorbid
condition is responsible for obesity, or if both are related
to some unmeasured third factor. One possibility is obesity
could directly contribute to the development of other health
problems. Diabetes is a good example of a direct complication
of obesity. A less obvious example is headache
frequency and severity, which have been shown to improve
if a patient loses weight.37
Furthermore, obesity has been
linked with increased prevalence of otitis media with effusion.
The proposed mechanisms for this include altered
cytokine expression, gastroesophageal reflux disease, or
fat accumulation.38
In some instances, causal relations
could run in both directions. For example, depression could
alter healthy eating and exercise patterns, whereas greater
weight gain could lead to more depression.39
A third possibility
is that obesity and comorbid conditions could share
common antecedent risk factors. For example, some
evidence suggests the relationship between obesity and
ADHD may be due to the experience of toxic stress in
the early years, resulting in alterations in executive function
that result in poor impulse control as well as leptin
insensitivity, which can contribute to weight gain.9,10
The
relationship between obesity and the development of
asthma is similarly complex, with causal arrows pointing
in both directions.40,41
It is noteworthy that the association of obesity with
ADHD was strong for those not taking stimulant medications,
but there were no associations for children taking
stimulants. This might suggest that children who are
untreated for their ADHD might have other risk factors
for obesity, or that stimulant medication reduces the
risk of obesity by decreasing appetite and improving
impulse control. Future longitudinal research is needed to
tease out the causal relationships embedded in these associations
and to explore whether associations remain with
control subjects for additional explanatory or confounding
factors.
Higher-weight-status categories were consistently associated
with more health problems. This has been found in
other studies.10,19
Obesity showed stronger and more
consistent relationships with other health problems than
overweight, which might be expected because
overweight is defined by individuals within a narrow
weight band (85th to <95th percentile of BMI), while
obesity is an unbounded category including the severely
obese. The relatively modest and less consistent
associations between overweight status and poorer health
could also arise because the overweight category is
likely to include individuals with high lean body mass
(eg, wrestlers, soccer players, football players) because
BMI does not specifically measure body fat contribution
to body weight.
Table 2. Prevalence of Health Problems by Childhood Weight Status for US Children Aged 10 to 17 From the 2007 National Survey of Children’s
Health*
Characteristic
Unweighted Sample
Size (N)†
Overall Prevalence,
% (95% CI)
Not Overweight,
% (95% CI)
Overweight,
% (95% CI)
Obese,
% (95% CI) c2
P
General health
Good/fair/poor health 43,287 16 (15–17) 13 (12–14) 16 (14–18) 30 (27–34) <.001
Activity restriction 43,240 7 (7–8) 7 (6–7) 7 (6–9) 11 (9–13) <.001
Psychosocial functioning
Internalizing problem 42,928 3 (2–3) 2 (2–3) 3 (2–5) 4 (3–6) <.001
Externalizing problem 43,160 11 (10–12) 9 (9–10) 13 (11–16) 15 (13–17) <.001
Repeat grade 43,219 12 (11–13) 10 (9–11) 12 (10–13) 20 (17–23) <.001
School problems 41,976 31 (30–32) 29 (27–30) 31 (29–34) 40 (37–43) <.001
$3 missed school days 42,832 48 (46–49) 46 (45–48) 49 (45–52) 53 (50–56) <.001
Mental health and developmental conditions
ADHD 43,106 9 (8–10) 8 (8–9) 9 (8–11) 12 (10–14) .003
Conduct disorder 43,248 4 (4–5) 3 (3–4) 5 (4–7) 7 (6–8) <.001
Depression 43,211 3 (3–4) 3 (2–3) 4 (3–5) 4 (3–5) .006
Anxiety 43,218 4 (3–4) 4 (3–4) 4 (3–6) 5 (4–6) NS
Learning disability 43,137 10 (9–11) 8 (8–9) 10 (8–12) 15 (13–17) <.001
Developmental delay 43,208 3 (3–4) 3 (2–3) 3 (2–5) 6 (5–8) <.001
Physical health condition
Good/fair/poor teeth 43,279 29 (28–30) 27 (25–28) 30 (27–33) 39 (36–42) <.001
Diabetes 43,271 0.7 (0.5–0.9) 0.7 (0.4–1.0) 0.5 (0.3–0.8) 0.9 (0.5–1.5) NS
Bone/joint/muscle problem 43,237 3 (3–4) 3 (2–3) 3 (2–4) 5 (3–7) .026
Asthma 43,202 11 (10–11) 9 (8–10) 12 (10–14) 15 (13–18) <.001
Allergies 43,192 27 (26–28) 26 (25–28) 29 (27–32) 30 (27–33) .025
Headaches 43,259 7 (6–7) 6 (5–7) 8 (6–10) 9 (7–11) .001
Ear infections 43,276 3 (2–3) 2 (2–2) 2 (2–3) 5 (4–7) <.001
$3 comorbid conditions 42,484 12 (11–13) 10 (9–11) 13 (11–15) 18 (15–21) <.001
CI ¼ confidence interval; ADHD ¼ attention deficit/hyperactivity disorder; NS ¼ not statistically significant.
*Percentages are weighted to be nationally representative.
†There is some variability in sample size as a result of missing data on comorbid health conditions.
10 HALFON ET AL ACADEMIC PEDIATRICS
Steep social gradients in obesity prevalence and attenuation
in coefficients when sociodemographic factors were
included in regression models suggest that social risk
factors contribute to some of the overlap between obesity
and other health problems. A strong age interaction effect
was found for diabetes, with associations becoming statistically
significant at ages 15 to 17. Although the relationship
between obesity and adult-onset diabetes is well estab-
lished,42–44
these data suggest the relationship between
obesity and diabetes is well under way beginning in
adolescence. There was also some evidence obesity might
have greater influence on health for higher-income or white
children. Other studies have noted similar findings,13,45,46
although the reasons are not clear. It could be that more
disadvantaged children face many other risk factors and
exposures, in addition to obesity, that take an even greater
toll on their overall health than their weight status.
Associations between weight status and repeating a grade
were independently associated with obesity and were not
explained by the presence of other measured comorbid
conditions. These findings are consistent with an emerging
literature demonstrating possible linkages between obesity
and lowered academic achievement measured by grade
point average, test scores, and performance motivation.47–50
Higher rates of obesity-associated internalizing and externalizing
behavior problems have also been noted in prior
clinical studies.51,52
Although we cannot address causal
mechanisms, there is a large literature linking childhood
overweight with risk factors for the development of
psychosocial problems, including weight-based teasing,
social stigmatization, and peer rejection.53–56
The strengths of this study lie in the large populationbased
nature of the NSCH, which allows us to present
the first comprehensive national profile examining associations
between weight status and a broad set of comorbid
conditions for US children. The main limitations are the
cross-sectional nature of the data and the reliance on
parental report of child height, weight, and comorbid
conditions. Previous research has shown a high correlation
between parent or self-reported and measured height and
weight for adolescents.57,58
Evidence from population
studies comparing prevalence estimates derived from
direct measurement versus parent report suggest fairly
good convergence for children aged 10 to 17.59
However,
analyses comparing prevalence rates by detailed age categories
between NSCH and National Health and Nutrition
Examination Survey (NHANES) suggest a possible overestimation
of obesity rates for children aged 10 to 11 and
underestimation of obesity rates for children aged 14 to
17, which may help explain the wider age differences in
obesity observed in NSCH.30
Because the obesity rates
did appear a bit high for 10- to 11-year-olds in our sample
compared to other studies, analyses were run excluding
these children, and the results were the same. Furthermore,
a comparison of the findings of our study with a wide range
of smaller-scale regional and clinic-based studies using
Table 3. Unadjusted and Adjusted Odds of Health Problems by Childhood Weight Status for US Children Aged 10 to 17 From the 2007
National Survey of Children’s Health
Characteristic
Unweighted
Sample
Size (N)†
Unadjusted Odds
(Reference ¼ Not Overweight) (95% CI) Adjusted Odds (95% CI)‡
Overweight Obese Overweight Obese
General health
Good/fair/poor health 43,287 1.30 (1.07–1.57)* 2.94 (2.44–3.56)* 1.09 (0.89–1.35) 2.18 (1.76–2.69)*
Activity restriction 43,240 1.15 (0.91–1.47) 1.79 (1.43–2.24)* 1.04 (0.81–1.32) 1.39 (1.10–1.75)*
Psychosocial functioning
Internalizing problem 42,928 1.67 (1.04–2.67)* 2.20 (1.44–3.35)* 1.43 (0.88–2.31) 1.59 (1.04–2.45)*
Externalizing problem 43,160 1.46 (1.14–1.87)* 1.65 (1.35–2.01)* 1.32 (1.02–1.71)* 1.33 (1.07–1.65)*
Repeat grade 43,219 1.15 (0.95–1.39) 2.14 (1.73–2.66)* 1.00 (0.82–1.23) 1.57 (1.24–1.99)*
School problems 41,976 1.12 (0.97–1.30) 1.65 (1.41–1.92)* 1.01 (0.87–1.17) 1.28 (1.08–1.50)*
$3 missed school days 42,832 1.10 (0.96–1.26) 1.30 (1.13–1.50)* 1.13 (0.99–1.30) 1.39 (1.20–1.61)*
Mental health and developmental conditions
ADHD 43,106 1.10 (0.89–1.37) 1.45 (1.15–1.83)* 1.07 (0.86–1.34) 1.29 (1.01–1.65)*
Conduct disorder 43,248 1.61 (1.15–2.26)* 2.15 (1.61–2.85)* 1.41 (1.00–2.00)* 1.50 (1.13–2.00)*
Depression 43,211 1.37 (1.01–1.87)* 1.51 (1.14–2.01)* 1.33 (0.98–1.82) 1.41 (1.04–1.93)*
Anxiety 43,218 1.21 (0.89–1.65) 1.33 (1.03–1.72)* 1.21 (0.88–1.65) 1.27 (0.95–1.70)
Learning disability 43,137 1.20 (0.93–1.55) 1.89 (1.52–2.35)* 1.12 (0.87–1.45) 1.57 (1.24–1.98)*
Developmental delay 43,208 1.25 (0.80–1.96) 2.37 (1.65–3.41)* 1.15 (0.74–1.79) 1.97 (1.38–2.81)*
Physical health conditions
Good/fair/poor teeth 43,279 1.17 (1.01–1.36)* 1.75 (1.51–2.04)* 0.94 (0.80–1.11) 1.14 (0.97–1.33)
Diabetes 43,271 0.71 (0.37–1.34) 1.32 (0.68–2.59) 0.74 (0.38–1.43) 1.47 (0.72–3.03)
Bone/joint/muscle problem 43,237 1.12 (0.80–1.55) 1.69 (1.09–2.61)* 1.16 (0.82–1.63) 1.83 (1.14–2.93)*
Asthma 43,202 1.35 (1.08–1.68)* 1.76 (1.42–2.17)* 1.30 (1.05–1.62)* 1.61 (1.28–2.03)*
Allergies 43,192 1.16 (1.00–1.35)* 1.19 (1.02–1.39)* 1.20 (1.03–1.39)* 1.28 (1.09–1.50)*
Headaches 43,259 1.41 (1.07–1.84)* 1.51 (1.18–1.93)* 1.43 (1.10–1.87)* 1.56 (1.21–2.01)*
Ear infections 43,276 1.71 (0.88–1.57) 2.69 (1.85–3.92)* 1.04 (0.77–1.40) 2.22 (1.55–3.17)*
$3 comorbid conditions 42,484 1.33 (1.07–1.63)* 1.86 (1.53–2.25)* 1.23 (0.99–1.52) 1.53 (1.24–1.89)*
CI ¼ confidence interval; ADHD ¼ attention deficit/hyperactivity disorder.
*Statistically signficant at P < .05.
†There is some variability in sample size as a result of missing data on comorbid health conditions.
‡Models include controls for child age, gender, race/ethnicity, parent education, household income, and family structure.
ACADEMIC PEDIATRICS OBESITY AND COMORBIDITY 11
other methods of case ascertainment, including clinical
assessment of weight status and comorbidity, revealed
a similar pattern and magnitude of associations between
obesity and a broad range of comorbid conditions such as
ADHD,29
asthma,22,23
orthopedic problems,25
head-
aches,27,60
and ear infections.28
This gives us confidence
that our estimates are valid reflections of comorbidity
patterns for US children.
CONCLUSIONS
The past 20 years have shown dramatic increases in the
prevalence of childhood obesity, with recent studies
showing that obesity has almost doubled between 1988
and 2006.3,61
This same time period has also shown large
increases in the prevalence of other childhood-onset health
conditions such as ADHD, conduct problems, learning
difficulties, and asthma.62,63
The finding that comorbid
conditions tend to cluster within individuals and that there
are common social risk factors that might contribute to
the development of both overweight and comorbid
conditions suggest the possibility of a common origin for
this shifting pattern of morbidity. We can speculate that
this major ongoing shift in the epidemiology of chronic
childhood health conditions is likely to be related to
recent shifts in the social and physical environment of
childhood, which includes more social and lifestyle risk
exposures.64
It also suggests that effective approaches to
preventing obesity are likely to have beneficial effects in
preventing related comorbid conditions.
Our findings suggest that obesity prevention efforts
should target the social determinants of obesity and related
comorbid health conditions. Our findings also suggest that
treatment of childhood obesity should include screening
for comorbid conditions that may require simultaneous
management. Our results indicate obese children are at
heightened risk of many different forms of suboptimal
health outcomes, and that early prevention and intervention
efforts are warranted to address concurrent health problems
as well as possible future health risks associated with childhood
obesity. Future research should seek to confirm the
associations reported in this study using clinical measures
of height and weight and longitudinal designs that allow for
the investigation of which conditions came first.
ACKNOWLEDGMENTS
Supported in part by funding from the Maternal and Child
Health Bureau of the Health Resources and Services Administration
Interdisciplinary Maternal and Child Health Training Program
(2 T76M600014:11) (Dr Halfon) and NIH LRP (Dr Larson). We also
thank Dena Herman, PhD, for her comments; Louba Aaronson, who
assisted with data analysis; and Amy Graber, who assisted with
document preparation.
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