Transcript Obesity in School-aged Children: Causes and Consequences

Cecilia Moore, MS, RD, LD
TTUHSC Department of Pediatrics
Lubbock, Texas
Objectives
 Identify at least 2 major lifestyle contributors to
overweight/obesity in the pediatric population 2-19
years of age.
 Evaluate the pros vs. cons of the clinical setting using
data from the TTUHSC Healthy Kids program.
 Compare the pros vs. cons of the school-based setting
as an intervention
Prevalence of Obesity* Among U.S. Children and Adolescents
(Aged 2 –19 Years)
National Health and Nutrition Examination Surveys
Data from NHANES I (1971–1974) to NHANES 2003–2006 show increases in overweight among
all age groups:
Among preschool-aged children, aged 2–5 years, the prevalence of obesity increased from 5.0%
to 12.4%.8, 46
Among school-aged children, aged 6–11 years, the prevalence of obesity increased from 4.0% to
17.0%.8, 46
Among school-aged adolescents, aged 12–19 years, the prevalence of obesity increased from
6.1% to 17.6%.8, 46
The 2007 national Youth Risk Behavior Survey
indicates that among U.S. high school students:
 Overweight
13% were obese.
 Unhealthy Dietary Behaviors
79% ate fruits and vegetables less than five times per day during the 7
days before the survey.
34% drank a can, bottle, or glass of soda or pop (not including diet soda
or diet pop) at least one time per day during the 7 days before the survey.
 Physical Inactivity
65% did not meet recommended levels of physical activity.
46% did not attend physical education classes.
70% did not attend physical education classes daily.
35% watched television 3 or more hours per day on an average school day.
25% played video or computer games or used a computer for 3 or more hours
per day on an average school day.
Reasons for the Prevalence of
Childhood Obesity
Genetic predisposition:
 Twin studies estimate that 65% to 75%
of the tendency to obesity is inherited.
Heritability of obesity greater than
schizophrenia, alcoholism and
atherosclerosis. Inheritance is mostly
polygenic and varies.
 Weight Set Point Hypothesis
Every individual has a genetically
inherited “set point ” that governs
“ideal” body mass.
Environmental factors influence this
set point and determine actual body
mass.
Environmental influences:
 Availability of high caloric density, palatable food. Since
the early 1900’s consumption of fats and sugars increased
by 67 and 64%, vegetables decreased by 26%.
 Advertising to children. On average a child sees 10,000 ads
a year and 90-95% are for sugared cereals, fast food, soda,
candy
 Portion Distortion: Serving Sizes are Growing
Several studies published in 2003 document increases in
portion sizes for many popular foods. This amounts to an
additional 50-150 calories per meal.
 Movement Towards a More Sedentary Lifestyle
Serving Sizes Then and Now
 Food or beverage
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1950s
French fries 2.4 ounces
Fountain soda 7.0 ounces
Hamburger patty 1.6 ounces
Hamburger sandwich 3.9 ounces
Muffin 3.0 ounces
Pasta serving 1.5 cups
Chocolate bar 1 ounce
Expanded 2003
up to 7.1 ounces
12 to 64 ounces
up to 8.0 ounces
4.4 to 12.6 ounces
6.5 ounces
3.0 cups
2.6 to 8 ounces
Rate of weight gain due to “extra”
calories
Rate of weight gain when calories
consumed equals calories required
for normal growth and
development.
50 calories per day over daily
requirement
100 calories per day over daily
requirement
IS OBESITY A DISEASE IN CHILDHOOD?
 Obesity is associated with insulin
resistance and metabolic syndrome
 65% of obese 5-10 year old children
have at least 1 cardiovascular disease
risk factor
 hypertension, hyperlipidemia,
abnormal glucose tolerance
 25% of obese 5-10 year old children
have 2 or more risk factors
Dietz
WH.JPediatr1999;134:535-536
Obesity: other associations and
complications
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Obstructive sleep apnea
Fatty liver disease with steatosis (NAFLD, NASH)
Orthopedic problems (SCFE, osteoarthritis)
Hypertension, pulmonary hypertension
GERD
Diabetes
Pubertal disorders
Chronic kidney disease
Polycystic ovary syndrome
Changing the Incidence of
Childhood Obesity - Society?
Very hard to effect “global change” when a majority of
the population either is not at risk or doesn’t
perceive it as “their problem”.
How can we outlaw video games when we can’t even
regulate more “obvious” health risks like cigarettes,
and alcohol?
Pediatric Weight Loss Programs in
Community
 Mostly hospital, or clinic-based. Some are franchised, for
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fee.
Education on healthy eating, parenting, behavioral
modification
Variable duration, curricula
High attrition rates (50-60%)
Lack of published data on effectiveness of intervention
Most do not involve significant exercise component (lack of
resources, liability issues)
Limited evidence of sustainability of weight loss
Expensive
Taking a look at a clinical intervention: Healthy
Kids Clinic
 Healthy Kids (overweight/obesity) clinic
 Texas Tech University Health Sciences Center
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Department of Pediatrics
 Lubbock, TX
 Established in 2006
 Purpose: to provide a clinical approach to the
childhood obesity epidemic in the area
Multidisciplinary Team
 Pediatrician/Pediatric Endocrinologist
 Registered Dietitian
 Psychology graduate student
 Exercise & Sports Sciences graduate student
Original Plan
 Appointments upon referral
 1st visit: meet entire team for assessment
 Bi-monthly follow-up visits with RD, and psychology
 Exercise opportunities twice a week
 Follow up visits with MD every 3 months
 Provide an individualized plan to aid in weight control
and implement healthy lifestyle changes for the entire
family
Issues along the way
 MOTIVATION!
 Bi-monthly visits
 Follow-up visits with MD
 Scheduling
 Graduate students – new students, new training,
different experiences
 Changes with the exercise portion of the intervention
– TTU Recreation Center, Fitness and Wellness
Clinic Trends: 2008-2009
 Collected data for 2 years
 Total referrals to Healthy Kids 2008: 130
 Total referrals for 2009: 138
 ~85% from Lubbock area
 ~15% from surrounding area
Percentage of referrals from different age groups
About 8 % of our referrals were siblings in 2008, and 5% in 2009.
Referrals: Gender
Ethnicity: Comparison of 2008-2009
Referrals: Ability to Schedule
Show Rate: Initial Visit
Follow-up rate
Weight Trends
 Randomly looked at 70 patients
 100% of those seen at their initial visit had BMI’s > 95th
percentile (highest: 53.8 kg/m2, 15 yo female, 51 kg/m2
17 yo male
 Success is individualized based on:
 Age: weight loss vs. weight maintenance
 BMI trends
 Compliancy with goals: were we able to make some
progress with changing lifestyle habits?
 Improvement in labs
Trends cont…
 About 20% of this group had some sort of success at
some point
 However, about 21% of these patients, when last seen,
had an increase in BMI
 Weight loss/maintenance was seen more in those who
visited once every 1-2 months
 When more time lapses between visits = more weight
gain!
Issues
 Individualized vs. group?
 MOTIVATION!
 Assessment of readiness-to-change is not occurring at
pediatrician’s office first
 Patience – takes time to get to goal
 Scheduling issues
 Clinic days
 Appointment times available
 Issues with the routine of how appointments are
scheduled
 Location/setting
Positives
 Multidisciplinary team
 Individualized
 Emphasizes family support
 Ability to recommend other subspecialty referrals
 An option that can work for some
The School Health Policies and Programs Study 2006
indicates that among U.S. high schools:
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Health Education
• 69% required students to receive instruction on health topics as part of a specific course.
• 53% taught 14 nutrition and dietary behavior topics in a required health education course.
• 38% taught 13 physical activity topics in a required health education course.
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Physical Education and Physical Activity
•95% required students to take physical education; among these schools 59% did not allow students
to be exempted
• 2% required daily physical education or its equivalent for students in all grades in the school for the
entire year.
•45% offered opportunities for students to participate in intramural activities or physical activity
clubs.
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School Environment
• 18%, students could purchase fruits or vegetables.
• 77%, students could purchase soda pop or fruit drinks that are not 100% juice.
• 50%, students could purchase chocolate candy.
• 52% did not allow students to purchase foods or beverages high in fat, sodium, or added sugars
during school lunch periods.
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Nutrition Services
• 77% offered a choice between 2 or more different fruits or types of 100% fruit juice each day for
lunch.
• 49% did not sell any fried foods as part of school lunch.
• 81% offered lettuce, vegetable, or bean salads a la carte
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Role of Schools in Preventing
Obesity
 Schools are a critical part of the social
environment that shape children’s
eating and physical activity patterns
 Lead by example: healthy food served
while at school, and limited access to
“junk food”
 Provide access to and maintain healthy
amount of physical activity while at
school
 Widen the school-home collaboration to
promote child’s physical health and
fitness
Percentage of secondary schools in which students could not be exempted from taking
required physical education for certain reasons*
14% - 50%
51% - 71%
72% - 79%
80% - 96%
No Data
*Enrollment in other courses, participation in school sports, participation in other school activities, participation in community sports
activities, high physical fitness competency test score, participation in vocational training, and participation in community service activities.
School Health Profiles, 2008
Percentage of secondary schools in which students could not purchase other kinds of candy
from vending machines or at the school store, canteen, or snack bar
23% - 63%
64% - 71%
72% - 83%
84% - 95%
No Data
School Health Profiles, 2008
Percentage of secondary schools in which students could not purchase salty snacks that are
not low in fat* from vending machines or at the school store, canteen, or snack bar
28% - 57%
58% - 64%
65% - 76%
77% - 91%
No Data
*Such as regular potato chips.
School Health Profiles, 2008
Percentage of secondary schools in which students could not purchase soda pop or fruit
drinks that are not 100% juice from vending machines or at the school store, canteen, or
snack bar
26% - 51%
52% - 62%
63% - 73%
74% - 93%
No Data
School Health Profiles, 2008
School-Based Interventions
 Boarding schools (Wellsprings Academy)
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and Summer camps (“fat camps”): very
effective, but not feasible for mainstream
School-based nutritional education
programs
Gaining popularity, however greatly
variable duration and curriculums
Published studies use BMI as outcome
measure
Most show none or modest improvements
in weight, BMI
Some show improved dietary habits
Little data on sustainability
Believed to be more effective than the
hospital-based programs due to peer
participation
An After School, Family-Centered Lifestyle Program: Collaboration Between Health Care Providers,
After-School program
Staff and Volunteers
7th Annual Forum for Improving Children’s Healthcare & National Congress on Childhood Obesity
Megan Lipton, MA, et al., 2008
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Methods
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The study took place over the 2006-2007 school year at
8 matched elementary schools in low-income school
districts in Los Angeles, San Jose, and Vacaville CA.
Population consisted of 325 child participants and 229
parents, of which full data was collected on 232
children.
Of these 232 individuals, 109 were in the intervention
group and 123 were in the control group.
Families at the intervention schools attended 6 weekly
3-hour classes consisting of didactic and interactive
nutrition education, exercise, parental support and
behavior change motivation.
Control schools families were tracked throughout the
year for comparison.
Adiposity measures, nutrition knowledge and eating
and physical activity behavior were measured.
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Results
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Overall students in the intervention group showed a
significant 6-week decrease in BMI z-score compared
to the control group, and a downward trend for body
fat percentage.
Neither the effect of intervention on decrease in BMI
z-score nor the downward trend for body fat
percentage in the intervention was affected/altered by
adjustment for age, gender, or school location.
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TABLE I. CHANGE IN BMI Z SCORE OVER 6 WEEKS
All Children (n=232)
P-value
Control (n=123) Intervention (n=109)
Mean Delta BMI Z
0.0364
-0.0588
p<0.0001
Std. Dev.
0.1664
0.1688
Children with BMI percentile
Mean Delta BMI Z
Std. Dev.
≥ to 85% (n=118)
P-value
Control (n=61) Intervention (n=57)
0.0062
-0.0349
p=0.0185
0.0991
0.0915
Children with BMI percentile
≥ to 90% (n=90)
P-value
Control (n=46) Intervention (n=44)
Mean Delta BMI Z
0.0148
-0.0413
p=0.0022
Std. Dev.
0.0925
0.0837
Why schools?
 Other than families, many aspects about the education
setting have a large influence on children’s lives
 Majority of time during the day is spent at school
 1-2 meals are provided
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1-2 snacks
 Where they will get their first official lesson on health,
nutrition, and physical activity
Issues
 Funding
 Adequate staff
 Food production contracts
 Medical issues of the individual might be missed
 Others?
Obesity Treatment: Basic Modalities
 Lifestyle intervention: utmost importance
 Clinical vs. school setting interventions
 Along with community assistance
 Medical therapies: reserved for severe obesity, very
limited pharmacological agents available for children.
Effective but results not sustainable
 Surgical treatment in cases with poor prognosis in
older adolescents