1. Obesity Interventions That Work
The Molten Moment
Double check graphs for C&P
Tracy Flood MD, PhD
Director of the Statewide Obesity Surveillance System
University of Wisconsin Madison

2. About Me

3. Social, Organizational Community, Public Policy
About Us
Individual
Social, Organizational
Community, Public Policy
Built environment
The
Socio Ecological Model
Cellular

4. Question:
How do we decrease obesity?
Clinic
1 v 1
Populations
vs.

5. Why? If rising OW/OB trends continue, by 2030 it will reach
Unhealthy
Weight Gain
Obesity
“Toxic” Obesity =
Metabolic
Syndrome
(MetS)
If rising OW/OB trends continue, by 2030 it will reach
16-18% of total health-care costs in the United States.
(Wang, Beydoun, Liang, Caballero, Kumanyika, 2008)
Currently, the world’s
leading causes of death
are the Atherosclerosis-related dz:
Ischemic heart disease (IHD)
Stroke
(Lopez & Mathers, 2006;
Mathers et al., 2009).
OW/OB  Increases Risk Factors
Risk Factors  Atherosclerosis
Atherosclerosis begins at a young age
Cardiovascular Dz
(CVD)
= Death

6. Goal Provide how-to-steps on how to move the needle on obesity &
prevent premature death from
cardiovascular disease.

7. Outline WHY should we care? Metabolic Syndrome, CVD, etc!
Ok, we care. Let’s take action!
Let’s Design an intervention that works (review the lit reviews)
WHEN = Molten Moment
WHERE = Clinic vs. Community
WHAT WORKS?*
*Informed by Biology The Story of the Fat Cell

8. When do we act?
The Molten Moment

9. The Molten Moment
Cold, Solid
HOT, Malleable

10. The Molten Moment
Where do you strike
For the biggest impact?

11. The Molten Moment Where do you strike For the biggest impact? birth 15
25+ 10 20
Age:
Where do you strike
For the biggest impact?

12. Where do we act? ?
The Molten Moment
Design an
Intervention

13. Pick an Obesity Intervention

14. Pick an Obesity Intervention
Individual
Organizational
(ex. Schools, worksites)
Policy &
Built environment

15. Will the Intervention work?
1000+ Studies
35 Systematic Reviews
& Meta-analyses
& What Works for Health
= Evidence-based
Interventions

16. Will the Intervention work?
Define “What Works”
Change
Key*
Behaviors
Obesity
CVD
MetS
*Will define key behaviors for each case

17. The Story of The Fat Cell
What Works? ?
The Molten Moment
The Story of The Fat Cell
Design an
Intervention

18. The Story of The Fat Cell

19. Little Cell, Big Problem
U.S. Prevalence of Overweight & Obesity %
Describe the incidence and prevalence of overweight and obesity from birth through adulthood
Pediatric Definition
Adult Definition
Data from NHANES Ogden, Carroll, Kit, Flegal 2014

20. Defining Obesity CHILDREN ADULTS Obese 30 Over- weight
Normalweight 30 25
Obese BMI ≥ 95th percentile
Overweight BMI 85th – 94th percentile
>
CHILDREN
ADULTS

21. The Story of The Fat Cell
BMI
The Story of The Fat Cell OB
Glucose spike OW
Glucose  Fat
insulin
Fat Cell NW
Stem Cells can become Fat Cells
(Arner Spalding 2010; Spalding, Arner 2008)

22. Let’s Begin!

23. Pick an Obesity Intervention
Normal weight 35 yo
with an obese preschooler
Obese 15 yo girl who is
otherwise healthy
Obese 55 yo man
with Metabolic Syndrome

24. with Metabolic Syndrome
Pick an Obesity Intervention
Diet +
Exercise
Good
Advice Rx
Obese 55 yo man
with Metabolic Syndrome

25. Results of Intervention
Advice Alone
13 lbs
Exercise Alone
Diet Alone
Orlistat
Diet+Exercise
Sibutramine
Very Low
Cal Diet
Average weight loss of subjects completing a minimum 1-year weight-management intervention; based on review of 80 studies (N=26,455; 18,199 completers [69%]). (Franz et al, 2007)
Note: Built environment & surgery not included

26. Results of Intervention
5’6”
weight
BMI OB
13 lbs
190 lb 30 OW
160 lb 25 NW

27. Meta-Analysis & Reviews
Behaviors:
Physical Act/
Active Transport
Balanced Diet
Multi-component Individualized programs
Weight
(~4-8 lbs) prevent wt
Obesity
Worksite Wellness
Programs
CVD
MetS
Built environment associated with active transport  weight loss and decreased CVD
CVD improves,
With minimal
weight loss?
Zoning for Active Living
(Mixed use, good streetscape)
Ref What Works for Health

28. The Story of The Fat Cell
Glucose spike
insulin
Stressed fat cells = Metabolic Syndrome
(Arner Spalding 2010; Spalding, Arner 2008)

29. The Story of The Fat Cell
Result:
Higher TG
Lower HDL
Fatty Liver
TG
HDL
TG
HDL is the good cholesterol
Scavenges Xtra TG then is destroyed FA FA
TG
TG (Fat)
Used for fuel if active
Origins of Metabolic Syndrome
(Arner Spalding 2010; Spalding, Arner 2008)

30. The Story of The Fat Cell
High TG, Low HDL
Hypertension
Diabetes
=Metabolic Syndrome
Insulin
Resistance
FAT

31. The Story of The Fat Cell
Insulin Resistance
Body
Type
& Risk
= Metabolic Syndrome

32. The Story of The Fat Cell
BMI
Obese
Normal
weight
Metabolic Health
Good
Poor

33. with Metabolic Syndrome
The Story of The Fat Cell
Obese 55 yo man
with Metabolic Syndrome

34. The Story of The Fat Cell
Glucose spike
insulin
Relief with 7-10% Weight Loss
(Arner Spalding 2010; Spalding, Arner 2008)

35. The Story of The Fat Cell
5’6”
I’m HUNGRY!!
BMI
I’m HUNGRY!!
FEED me!! OB 30 OW 25
Rebellion with >10% Weight Loss
(Arner Spalding 2010; Spalding, Arner 2008) NW

36. The Story of The Fat Cell
I’m HUNGRY!!
FEED me!!
EAT MORE!
BURN LESS!
Rebellion with >10% Weight Loss
(Martins, Robertson, Morgan 2008)

37. 30 min of moderate exercise x 5 days a week to maintain
x 7 d/wk to maintain weight loss
lebeauleblog.wordpress.com
I’m HUNGRY!!
FEED me!!
(Martins, Robertson, Morgan 2008)

38. The Molten Moment
Behavior Change
Modest Weight
CVD Risk Decreases

39. Behavior Change Possible
The Molten Moment
Behavior Change Possible
CVD Risk Decreases
birth 15
25+ 10 20
Age:

40. Pick an Obesity Intervention
Normal weight 35 yo
with an obese preschooler
Obese 15 yo girl who is
otherwise healthy
Obese 55 yo man
with Metabolic Syndrome

41. Pick an Obesity Intervention
School
based
Behav
Therapy
Neighbor-
hood
Obese 15 yo girl who is
otherwise healthy

42. Results of Intervention
Adult
Obesity

43. Meta-Analysis & Reviews
Behaviors:
Physical Act
Sedentary Behav (SB)
Sugar-Sweetened Beverage
Individualized Behav programs
Clinic-based counseling (SB)
Weight gain
TV Monitoring Devices (SB)
Obesity
Multi-Component School-based
Enhance/Expand Physical Ed
Physically Active Classrooms & Structured Recess
But will she
remain obese
for life?
Reductions in sedentary Behavior
BMI changes with intense behaviroal
Policy & envi  diet & PA
CVD
MetS
Competitive Pricing in Schools
Safe Routes to School
& Walking Schoolbus
Access to Places for PA
(Mixed use, streetscape, Rec Facilities)
What Works For Health
N=13 meta-analysis &
Systematic reviews

44. The Story of The Fat Cell

45. Finished w/ Linear Growth
The Story of The Fat Cell
Very High Risk of
Future CVD
Trajectory above the 75th percentile Ventura, Loken, & Birch (2009)
Link between Childhood
BMI and adult CV death
Begins as early as:
8 yo in boys
13 yo in girls
BMI child  CIMT adult. Further adjustment for adult cardiovascular risk factors did not change the relationship (linear regression coefficient=2.1 microm/s.d.; 95% CI: 1.0; 3.1) between adult (28 yo) CIMT and adolescent BMI. Adjustment for adult BMI attenuated the association (linear regression coefficient=0.9 microm/s.d.; 95% CI: -0.3; 2.2) as the majority of overweight and obese adolescents remained overweight or became obese young adults. (Oren et al., 2003).
Elevated BMI in boys as early as 8 and girls as early as 13 is significantly associated with developing metabolic syndrome at >or=30 years. OR y/o males 1.8 (1.3, % CI) and females 2.8 (1.9 to 4 95% CI). However, “elevated” BMI is along the 75th%ile of boys’ CDC chart and girls th percentile…. much much lower than the Expert Committee cutoffs. (Sun, Liang, Huang, Daniels, et al 2008)
Denmark: Childhood BMI (7-13 y/o boys, y/o girls) is associated with adult CHD (a fatal or nonfatal event) (adult >=25 y/o). As BMI increased, the risk increased. Each 1 unit increase in BMI (5.6 kg (12.3 lbs) boys, 6.3 kg (13.9 lbs) girls) increased the risk for fatal cardiac events with a hazards ratio adjustede for bw, in 13 y/o boys (HR 1.24) and girls (HR 1.23) (Baker, Olsen, Sørensen, 2007).
BMI at 13 y/o predicts cholesterol and glucose resistance in adulthood (Steinberger, Moran, Hong 2001)
 ‘Overweight’ in adolescents (13-18 y/o) predicts CHD morbidity in men and women (Must, Jacques, Dallal, Bajema, Dietz,1992). Harvard Longitudinal Study to Overweight=”75th percentile in subjects of the same age and sex in a large national survey”
 ‘Overweight; in adolescents (13-18 y/o) predicts mortality in men (not women): RR of 1.8 for all-cause mortality and 2.3 RR for CHD mortality. (Must, Jacques, Dallal, Bajema, Dietz, 1992). Harvard Longitudinal Study to Overweight=”75th percentile in subjects of the same age and sex in a large national survey”
 Norway: 227, y/o followed for 31.5 years. Increased risk of mortality became apparent after the age of 30. (Engeland, Bjorge, Sogaard, Tverdal 2003)
- Mortality in males (vs. 25th-75%iles CDC charts):
-85-95% 30% increased risk
->95% 80% increased risk
- Mortality in females
->95% 100% increased risk
 White-black cohort of Bogalusa Heart Study y/o Srinivasan SR, Bao W, Wattigney WA, Berenson GS. Teenage OW (BMI>=75%ile (as compared to 25-50th%ile)) increases risk of adulthood(27 to 31 y/o):
- Hypertension: Prevalence increased 8.5-fold
- Dislipidemia: Prevalence increased 3.1 to 8.3-fold
Finished w/ Linear Growth
Increased BMI =
Increased Risk of CVD
CVD Risk: Sun et al., 2008
Trajectory: Ventura, Loken, & Birch, 2009

46. DECREASE Mortality risk in adulthood for OW/OB adolescents
If OW/OB teen Normal Weight by adulthood
Risk Factors & Atherosclerosis associated with adiposity
DECREASE
(Oren et al., 2003; Weiss et al., 2009)
But our patient has a 92% chance
of remaining obese at the age of 40.
(Nader, 2008)
Trajectory above the 75th percentile Ventura, Loken, & Birch (2009)
Link between Childhood
BMI and adult CV death
Begins as early as:
8 yo in boys
13 yo in girls
BMI child  CIMT adult. Further adjustment for adult cardiovascular risk factors did not change the relationship (linear regression coefficient=2.1 microm/s.d.; 95% CI: 1.0; 3.1) between adult (28 yo) CIMT and adolescent BMI. Adjustment for adult BMI attenuated the association (linear regression coefficient=0.9 microm/s.d.; 95% CI: -0.3; 2.2) as the majority of overweight and obese adolescents remained overweight or became obese young adults. (Oren et al., 2003).
Elevated BMI in boys as early as 8 and girls as early as 13 is significantly associated with developing metabolic syndrome at >or=30 years. OR y/o males 1.8 (1.3, % CI) and females 2.8 (1.9 to 4 95% CI). However, “elevated” BMI is along the 75th%ile of boys’ CDC chart and girls th percentile…. much much lower than the Expert Committee cutoffs. (Sun, Liang, Huang, Daniels, et al 2008)
Denmark: Childhood BMI (7-13 y/o boys, y/o girls) is associated with adult CHD (a fatal or nonfatal event) (adult >=25 y/o). As BMI increased, the risk increased. Each 1 unit increase in BMI (5.6 kg (12.3 lbs) boys, 6.3 kg (13.9 lbs) girls) increased the risk for fatal cardiac events with a hazards ratio adjustede for bw, in 13 y/o boys (HR 1.24) and girls (HR 1.23) (Baker, Olsen, Sørensen, 2007).
BMI at 13 y/o predicts cholesterol and glucose resistance in adulthood (Steinberger, Moran, Hong 2001)
 ‘Overweight’ in adolescents (13-18 y/o) predicts CHD morbidity in men and women (Must, Jacques, Dallal, Bajema, Dietz,1992). Harvard Longitudinal Study to Overweight=”75th percentile in subjects of the same age and sex in a large national survey”
 ‘Overweight; in adolescents (13-18 y/o) predicts mortality in men (not women): RR of 1.8 for all-cause mortality and 2.3 RR for CHD mortality. (Must, Jacques, Dallal, Bajema, Dietz, 1992). Harvard Longitudinal Study to Overweight=”75th percentile in subjects of the same age and sex in a large national survey”
 Norway: 227, y/o followed for 31.5 years. Increased risk of mortality became apparent after the age of 30. (Engeland, Bjorge, Sogaard, Tverdal 2003)
- Mortality in males (vs. 25th-75%iles CDC charts):
-85-95% 30% increased risk
->95% 80% increased risk
- Mortality in females
->95% 100% increased risk
 White-black cohort of Bogalusa Heart Study y/o Srinivasan SR, Bao W, Wattigney WA, Berenson GS. Teenage OW (BMI>=75%ile (as compared to 25-50th%ile)) increases risk of adulthood(27 to 31 y/o):
- Hypertension: Prevalence increased 8.5-fold
- Dislipidemia: Prevalence increased 3.1 to 8.3-fold
Figure. Mortality in adulthood (<55 y/o) of OW/OB adolescents (males and females) compared to normal weight peers.
Note: Subjects with BMI 25th to 75th percentile (CDC charts) were the referent group.
Adapted from Bjorge, Engeland, Tverdal, & Smith (2008).

47. The Story of The Fat Cell
The Immortal Cell… sort of
(Arner Spalding 2010; Spalding, Arner 2008)

48. The Molten Moment Behavior Change Possible Behavior Change Possible
Altered growth trajectory
Decrease CVD Risk
birth 15
25+ 10 20
Age:

49. Pick an Obesity Intervention
Normal weight 35 yo
with an obese preschooler
Obese 15 yo girl who is
otherwise healthy
Obese 55 yo man
with Metabolic Syndrome

50. with an obese preschooler
Pick an Obesity Intervention
Early
childcare
based
Behav
Therapy
Neighbor-
hood
Normal weight 35 yo
with an obese preschooler

51. Results of Intervention

52. Meta-Analysis & Reviews
Behaviors:
Sugar-Sweetened Beverage
Provision of Health Food &
Removal of Unhealthy Food
Sedentary Behavior
Sleep
Intervention to reduce SB
Obesity
Nutrition & PA Interventions in Preschool & Early Childcare
Allow me to
Explain
CVD
MetS
Access to Places for PA
(Mixed use, streetscape, Rec Facilities)
What Works For Health
N=13 meta-analysis &
Systematic reviews

53. The Story of The Fat Cell

54. The Story of The Fat Cell
I’m Learning about the world!
Sugar-sweetened beverages
Skipping Meals
Sedentary Behavior
Sleep
Fat Cell of a Preschooler

55. Behavioral Plasticity
Preschoolers mimic parents’:
Fruit & Vegetable consumption
Portion sizes
Snacking frequency TV
Physical activity
Grocery shopping
“When mothers improve their diets in order to control their weight, their child
(1-3 y/o) improves their diet as well, even if that was not the original intent”
(Klohe-Lehman, et al., 2007)

56. Synthesis of Evidence

57. Synthesis: Behavior
(Wahi, et al., 2011) Meta-Analysis. RCT to reduce SB. 13 studies in review

58. Synthesis: BMI Change 6-12 yo OB OB OB ns OW OW OW NW NW NW
(Waters, et al., 2011)
Cochrane review of 55 studies. Meta-analysis on 37 studies, 27,946 children.

59. Synthesis: Success
Intervention Success Rates defined as enough BMI change to reduce CVD risk
Danielsson et al., 2012 (0.5 SD BMI)
Kraschnewski et al., 2010

60. BMI
Percentile
Chart
Behavior
BMI Change
Success

61. Thinnest Weight
Borderline
Risk
High Risk
Moldable Habits
Successful Community Interventions

62. The Molten Moment Behavior Change Possible Behavior Change Possible
 Obesity
Alter growth trajectory
Decrease CVD Risk
birth 15
25+ 10 20
Age:
MOLTEN MOMENT
Prevention of Obesity

63. New Goal Provide how-to-steps on how to move the needle on obesity &
prevent premature death from
cardiovascular disease.
behavior &

64. Summary Obesity is associated with MetS, CVD, & Death
Small changes at any time = CVD
Small changes at the Molten Moment = Obesity
The 1v1 AND Population Interventions work
We must all work together, doing what we can

65. FOR MORE INFORMATION: What Works for Health County Health Rankings.org

66. Thank You!
Questions/Comments?
For M