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The Evidence for Obesity Prevention In
Primary Care: TARGeting Kids!
Catherine S Birken MD, MSc, FRCPC
The Applied Research Group for Kids!
Conflict Disclosure Information:
Presenter: Catherine Birken MD, MSc, FRCPC
Title of Presentation: The Evidence for Obesity
Prevention in Primary Care: TARGeting Kids
I have no financial or personal relationships to disclose
Objectives
• Outline Evidence for Obesity Prevention
Strategies in Primary Care
BMI screening
Determinants of childhood obesity
Effective prevention interventions
• Demonstrate an understanding of practice
based research networks - TARGet Kids!
The Case
• A 5 year old boy is scheduled for his annual
well-child visit at his primary care physicians
office
• His mother tells the physician that she has
struggled herself with obesity and is worried
about her son’s weight
What should the physician do next?
Is Obesity A Problem in Young
Children?
• Obesity rates are high and increasing
• Obesity in childhood associated with
obesity in adults
• Risk of comorbidities in childhood
• Risk of cardiovascular disease and
diabetes in adults
Is Obesity a problem in children?
NHANES, 2011
CHMS, 2012
Start in the Early Years
Healthy growth and development,
beginning in the early childhood years may
be associated with health throughout life
Developmental Origins of
Disease
Fetal development and
and early childhood in
particular the interactions
between mother and
developing child, impact
the rest of life
Opportunities for impact:
Primary Health Care
• Primary health care includes primary care
services, health promotion and disease
prevention
• Physicians are a trusted source of
information and guidance
• Children attend frequently
– 30% of child visits in the US (Moyer, 2001)
– 19 visits in first 2 years in Ontario (Guttmann,
2006)
Leveraging the Publically
Funded Immunization Schedule
• Start early: all kids on the path to
health
Leverage well-baby and
childhood immunization visits to
promote healthy weights and
enhance surveillance and early
intervention
• Change the food environment
• Create Healthy Communities
MOHLTC: Healthy Kids Panel Recommendations 2013
Fill the Gaps
There are critical gaps in knowledge
needed to promote child health in the
primary care setting
• Development and use of evidence-based
recommendations for preventive care is
challenging
• Most child health recommendations are
Grade ‘I” - insufficient evidence
• Lack of high quality screening and
counseling studies in primary care for
children
Practice Based Research Network
www.targetkids.ca
Practice Embedded Data Collection
LABORATORY SERVICES
Mount Sinai Services
DATA MANAGEMENT
SYSTEM
Applied Health Research
Centre
Secure web-based data
management using
Medidata RAVE™ software
Primary Healthcare Practice Age newborn to 5 years
Height, weight, BMI
waist circumference,
blood pressure,
head circumference,
parent BMI
Questionnaires
Laboratory
tests
A research assistant trained in phlebotomy is
embedded in each practice site
Village Park
Paediatrics
Dr. Eddy Lau
Dr. Brian Chisamore
Dr. Sharon Naymark
Tarandeep Malhi (RA)
Clairhurst Paediatrics
Dr. Michael Peer
Dr. Sheila Jacobson
Dr. Carolyn Taylor
Subitha Rajakumaran
(RA)
Danforth Paediatrics
A
Dr. Patricia Neelands
Dr. Janet Saunderson
Dr. Anh Do
Laurie Thompson (RA)
Danforth
Paediatrics B
Dr. Marty Perlmutar
Dr. Karoon Danayan
Dr. Alana Rosenthal
Juela Sejdo (RA)
St Michael’s Hospital
410 Sherbourne
Family Medicine
Clinic
Dr. Susan Shepherd
Nadia Kabir (RA)
Research Leads: Dr. Patricia Parkin
Dr. Catherine Birken
Dr. Jonathon Maguire
Research
Managers/Coordinators: Kanthi Kavikondala
Matthew D’Ascanio
Steering Committee: Dr. Mark Feldman
Dr. Moshe Ipp
Dr. Brian Chisamore
Dr. Tony Barozzino
LABORATORY
SERVICES Mount Sinai Services
Dr. Azar Azad
DATA MANAGEMENT Applied Health Research Centre
Dr. Muhammad Mamdani
Magda Melo
Kevin Thorpe
Dr. Gerald Lebovic
Yang Chen
St Michael’s Hospital
Pediatric Ambulatory
Clinic
Dr. Tony Barozzino
Dr. Michael Sgro
Dr. Sloane Freeman
Tonya D’Amour (RA)
St Michael’s
Hospital
80 Bond Street
Family Medicine
Clinic
Dr. Nav Persaud
Richa Kukkar (RA)
Humber Paediatrics
Dr Peter Wong
Dr Robert Lau
Dr Barbara Smiltnieks
Dr Keewai Fung
Dr Michael Dorey
A Platform for Understanding Growth
and Health Behaviour Trajectories
Time Gro
wth
and H
ealth B
ehavio
urs
A Platform for Randomized Trials
random
ize Group A
Group B
Building Linkages
Obesity prevention strategies
in primary care
BMI screening
Determinants of childhood obesity
Effective prevention interventions
Measuring Growth in Primary Care
Body Mass Index:
weight/height2 (kg/m2)
How Should Physicians Screen for Obesity?
US Preventive Services Task Force (2010):
• Screen children 6 years and older using BMI
• No evidence for under 6 years
Canadian Preventive Task Force Guide (2013)
• TBA
Rourke Baby Record, Greig Record
• Height and weight at each well-child visit
PROMOTING OPTIMAL MONITORING OF CHILD
GROWTH IN CANADA: USING THE NEW WHO
GROWTH CHARTS (Pediatrics and Child Health, 2010)
• Based on the Multicentre Growth
Reference Study (2006)
• Monitor growth in ideal growth
conditions – prescriptive curves
• Endorsed by Dieticians Canada,
Canadian Paediatric Society,
College Family Physicians
Canada
• Other curves – CDC, IOTF cut
offs not recommended
Do Primary Care Physicians
Measure growth?
• 80% well-child visits in US: documented
height and weight (Clinical Pediatrics, 2011)
• 36% US physicians have knowledge of BMI
guidelines n=716 (Prev Med 2011)
What are solutions?
Randomized Controlled Trial of a
Mailed Toolkit to Increase Use of Body Mass Index
Percentiles to Screen for Childhood Obesity (Public health Research, 2009)
Obesity Prevalence using
Electronic Medical Records
• Abstraction of BMI data from EMRs used
to estimate prevalence and outcomes in
US, Sweden
• The uptake of EMRs is increasing in
Canada
• Can we use EMRs?
Overweight and Obesity in Children in Ontario
using Electronic Medical Records Catherine Birken, Karen Tu, William Oud, Sarah Carsley, Miranda Hanna, Gerald Lebovic,
and Astrid Guttmann.
Objectives:
• To determine the frequency of height and weight
documentation in EMRs in children
• To describe the prevalence of childhood
overweight and obesity, by age, and sex using
data collected in the Electronic Medical Record
Administrative data Linked Database (EMRALD)
database in Ontario.
Methods
• Sample-children with at least one well-
child visit from Jan 2010 to Dec 2011
• Most recent well-child visit with both height
and weight selected
• Proportion, and 95% CIs of subjects
defined as overweight, and obese, by age
group and sex
• Chi squared tests to compare rates by age
group and sex
All Rostered Children
in EMRALD1 (n=31,637)
N (%)
All Rostered Ontario
Children2 (n=2,025,159)
N (%)
All Ontario Children
(n=3,122,918) N (%)
Sex Male 16,052 (50.7) 1,031,460 (50.9) 1,601,593 (51.3) Female 15,582 (49.3) 993, 699 (49.1) 1,521,325 (48.7)
Age group 0-4 8,218 (26.0) 335,013 (16.5) 727,088 (23.3) 5-9 7,928 (24.6) 484,587 (23.9) 747,225 (23.9) 10-14 7,772 (24.4) 558,186 (27.6) 779,141 (25.0) 15-19 7,719 (25.1) 647,373 (31.9) 869,464 (27.8)
Neighborhood Income 3 1 – Lowest Quintile 4838 (15.3) 358,472 (17.7) 595,712 (19.1) 2 5597 (17.7) 374,091 (18.5) 576, 662 (18.5) 3 6480 (20.5) 418,112 (20.6) 625,302 (20.0) 4 7231 (22.9) 452,306 (22.3) 678,401 (21.7) 5 – Highest Quintile 7416 (23.4) 414,356 (20.5) 634,259 (20.3) Unknown/missing 75 (0.2) 7822 (0.4) 12,582 (0.4)
Rurality3 Rural 6058 (19.2) 117,113 (5.7) 149,605 (4.8) Suburban 9859 (31.2) 370,665 (18.3) 467,531 (14.9) Urban 15,720 (49.7) 1,537,381 (75.9) 2,505,782 (80.2)
Baseline Characteristics of Children in EMRALD
1Administrave data on patient demographics were available were available for 31,637 of the 33,343 (95%) children n EMRALD3Neighborhood income quintile and rurality were calculated by linking postal code from the Registered Persons Database to 2006 Statistics Canada Census data.
Are heights and weights
measured at visits?
• 32% of all child visits had documented
height and weight
– Higher rate in younger children
• 84% of health maintenance visits had
height and weight documented
– No differences by age
Prevalence of Overweight and Obesity in
Electronic Medical Records
in Ontario, by age
Submitted, 2013
n BMI Overweight
Prevalence
Obese
Prevalence
Mean SD % 95% CI % 95% CI
Overalla
<1 1195 16.0 2.0 12.1 10.2-13.9 2.3 1.4-3.2 1-4 3426 16.3 1.6 26.1
† 24.6-27.6 6.1
† 5.2-6.9
5-9 1445 16.4 2.5 23.7 21.5-26.0 9.0† 7.5-10.5
10-14 977 20.0 4.3 31.8† 28.9-34.8 12.0* 9.9-14.1
15-19 662 22.9 4.6 28.7 25.2-32.2 9.4 7.1-11.7
What is the prevalence of overweight
and obesity in children in Canada?
Canadian Health Measures Survey
• National Study of Canadians 3-79 years • Includes Children 3-18 years n=2200 • Survey and health measures • Less than 300 children 3-5 years of age
in 2011
BMI in Canadian Children:
Canadian Health Measures Survey
Prevalence of Overweight and Obesity in
Preschool Children in TARGet Kids!
Sex Age
group N (%)
Overweight
% 95% CI
Obese
% 95% CI
All 2-5 2091 17.6 16, 19.3 5.1 4.2, 6.1
Male 2-5 1070 (51.2) 18.9 16.6, 21.4 5.3 4.1, 6.9
Female 2-5 1021 (48.8) 16.3 14.1, 18.7 4.8 3.6, 6.3
Canadian Obesity Network presentation, 2013
Subjects recruited 2008-2011
Three Approaches to Data Collection
Characteristics
Canadian Health
Measures Survey
Electronic Medical
Records
Practice Based
Research Network
Representative National RegionalNational RegionalNational
Sample size Small Large Large
Age Excludes 0-3 all all
Design Cross-sectional Longitudinal Longitudinal
Measure Health
outcomes
Yes Limited Yes
Evaluate
Interventions
Limited Health system and
population level
interventions
Trials
Measure health
behaviours
Yes No Yes
Evaluating Determinants of
Childhood Obesity in Primary
Care Settings
• Nutritional Risk • Neighourhood influences
Nutrition Screening Tool for Every
Preschooler : The NutriSTEP®
• Nutrition risk screening questionnaire
– 17 parent completed questions
• Validated in preschoolers in Ontario
– dietician assessment
– 3 day food records
• Topics: food intake, eating behaviours,
parent perceptions of growth and activity
The NutriSTEP® and
Cardiovascular Risk
Research question:
• Are eating behaviours associated with
cardiovascular risk, as measured by non-
HDL Cholesterol?
Methods:
• Cross sectional study of NutriSTEP and
non-HDL C
• 1076 3-5 year olds from TARGet Kids!
Cardiovascular risk associated with eating
behaviours during early childhood
CMAJ, 2013
NutriSTEP® and Primary Care
• Is this enough evidence to
recommend use in primary care?
• Next Steps:
– Examine metabolic outcomes
– Examine micronutrient deficiency (Iron,
Vitamin D)
– Examine associations with growth
trajectories
THE WEIGHT OF PLACE THE ROLE OF NEIGHBORHOOD ON CHILDHOOD
OBESITY: A TARGET KIDS! STUDY
Morinis J, Gozdyra P, Lebovic G, Carsley S, Maguire J,
Parkin P, Gillman M, Glazier R, Birken CS
Objectives
• To determine if the neighbourhood activity
friendly index is associated with zBMI in early
childhood, after adjustment for individual level
risk factors
• Cross sectional study evaluating two unique
data sources in Toronto, Canada
– Validated measures of neighbourhood
determinants of health from Centre Research
Inner City Health, SMH
– Individual level data from TARGet Kids! cohort
Activity Friendliness and Child zBMI
• Multivariate analysis for AFI and zBMI (p=0.02)
• Adjusted for confounding variables - child, parent factors, neighbourhood income
Presented PAS May, 2013
AFI quintile zBMI, mean (SD)
1 (low friendliness) 0.269 (1.088)
2 0.214 (1.022)
3 0.131 (1.053)
4 0.118 (1.049)
5 (high friendliness) 0.063 (1.109)
Obesity Prevention
Interventions in Primary Care
• RCTs for a single health behaviour • RCTs for complex behaviour
Screen Time
Preschool children watching 3-5 hours
of screen time/day (Certain, 2002)
Screen time associated with
overweight at age three; Odds Ratio:
2.61 (Lumeng, 2006)
Intervention: 10 minute‘doc talk’at 3 year old visit
reduce screen time
remove screen from bedroom
turn off TV during meals
RCTs for Early Childhood,
multiple behaviours
Primary care intervention (Taveras, 2012)
Nursing home visits (Wen, 2012)
Parent educator home visits (Haines, 2013)
• Overweight or obese 3-7 year olds
• 4 additional visits, 3 phone calls
• Restructured primary healthcare chronic care model
Intervention:
8 public health home nurse visits
Breast is best
No solids for me until 6 months
I eat a variety of fruit and vegetables every day
Only water in my cup
I am part of an active family
Results
• BMI decreased by -0.38 (-0.68, -0.08); p=0.01
Home based intervention: 2-5 year olds
• Motivational coaching home visits, phone calls,
text messages
– Family meals, adequate sleep, limit TV time, remove
TV bedroom
• 6 month outcomes:
– BMI -0.4 (-0.79, 0.00; p=0.05)
– TV weekend (-1.1 hr/d (-1.9, -1.15; p=0.02)
– Sleep increased (0.75 hrs/day; 0.06, 1.44; p=0.03)
NEXT STEPS FOR
TARGet Kids!
Studies:
• BMI trajectories and health outcomes
• RCT obesity prevention interventions
Network:
• build capacity, develop partnerships,
establish models for funding
MOHLTC: Healthy Kids Panel
Recommendations 2013
Use evidence, monitor progress, ensure
accountability
•Develop a surveillance system to monitor weights,
risk factors, protective factors over time.
•Support research on the causes of childhood
overweight and obesity and effective intervention
•Establish a mechanism to monitor the
implementation and impact of the strategy
•Report annually to the public on progress in
meeting Ontario’s target.
Back to the Case
• A 5 year old boy is scheduled for his annual
health maintenance visit at his primary care
physicians office
• His mother tells the physician that she has
struggled with obesity and worries about her son
• What should the physician do next?
Back to the Case
Engage and Assess
•Measure BMI WHO -85% for age, sex
•NutriSTEP score – moderate risk
– Meals in front of the screen, 3-4 cups/day of
juice, concerns re neighbourhood safety
Plan
•Small achievable family goals
•Consider referral to dietician
•Arrange a follow up appointment
Questions and Answers
Funders
Research Institutes
Research Personnel
Doctors Nurses and Office Staff
Children and Families
Thank You!
www.targetkids.ca
Sample:
Overweight preschool
children
Intervention:
10 group sessions; 8 phone
follow up calls
Restrict calories, reduced
screen time; weekly weights
Results – reduced zbmi
TARGet Kids! Child Health
Indicators Indicator Mean(SD) N %Age 31.8(18.7)
Sex
Male 2500 52.50
Breastfeedinginitiation(Everbreastfed?) 4321 93.0
Breastfeedingduration 10.7(6.7)
ChildfreeplayMedian(IQR)
59.40(59.25)45.0(30-65)
Screentime**(child)
Median(IQR)
77.84(80.77)
60.0(28-107)
Vegetableandfruitconsumption**(Y/N) Vegetable(Eateninthelast3days) 898 83.46
Fruit(Eateninthelast3days) 918 86.12
Filling in the Gaps “Measuring the Health of Infants, Children and Youth for Public Health Ontario: Indicators, Gaps and Recommendations for Moving Forward”
Indicator Mean (SD) N %
Age 31.8 (18.7)
Sex
Male 2500 52.50
Breastfeeding Initiation (Ever breastfed?) 4321 93.0
Breastfeeding duration 10.7 (6.7)
Child free play
Median (IQR)
59.40 (59.25)
45.0 (30-65)
Screen time**(child)
Median (IQR)
77.84 (80.77)
60.0 (28-107)
Vegetable and fruit consumption** (Y/N)
Vegetable (Eaten in the last 3 days)
Fruit (Eaten in the last 3 days)
898
918
83.46
86.12
