Obesity Medicine Epidemiology & Pathophysiology

Treatment Options – Efficacy & Safety Benefits of Weight Loss Therapy

Maria Collazo-Clavell, MD W. Timothy Garvey, MD, PhD (moderator) Daniel L. Hurley, MD

Endocrine University at Mayo Clinic, Rochester, MN 24 March 2015

OBESITY MEDICINE: EPIDEMIOLOGY & PATHOPHYSIOLOGY

Dr. Maria Collazo-Clavell

Learning Objectives

• Understand public health burden and social costs of obesity

• Understand the pathophysiology that protects body weight against weight loss

• Understand the interactions among weight gain, insulin resistance, adipose distribution and inflammation and cardiovascular disease

• Understand why obesity is a disease

Prevalence of Self-Reported Obesity Among

U.S. Adults by State and Territory

Definitions

Obesity: Body Mass Index (BMI) of 30 or higher.

Body Mass Index (BMI): A measure of an adult’s weight in relation to his or her height, calculated by using the adult’s weight in kilograms divided by the square of his or her height in meters.

Prevalence of Self-Reported Obesity Among

U.S. Adults by State and Territory

Source of the Data

The data were collected through the Behavioral Risk Factor Surveillance System (BRFSS), an ongoing, state-based, telephone interview survey conducted by state health departments with assistance from CDC.

Height and weight data used in the BMI calculations were self-reported.

Prevalence of Self-Reported Obesity Among

U.S. Adults by State and Territory

BRFSS Methodological Changes Started in 2011

New sampling frame that included both landline and cell phone households.

New weighting methodology used to provide a closer match between the sample and the population.

Prevalence of Self-Reported Obesity Among U.S. Adults by State and Territory

Exclusion Criteria Used Beginning with 2011 BRFSS Data

Records with the following were excluded:

Height: <3 feet or ≥8 feet

Weight: <50 pounds or ≥650 pounds

BMI: <12 kg/m2 or ≥100 kg/m2

Pregnant women

Prevalence¶ of Self-Reported Obesity Among

U.S. Adults by State and Territory, BRFSS,

2011

¶ Prevalence estimates reflect BRFSS methodological changes started in 2011. These estimates should not be

compared to prevalence estimates before 2011.

*Sample size <50 or the relative standard error (dividing the standard error by the prevalence) ≥ 30%.

Prevalence¶ of Self-Reported Obesity Among

U.S. Adults by State and Territory, BRFSS,

2014

¶ Prevalence estimates reflect BRFSS methodological changes started in 2011. These estimates should not be

compared to prevalence estimates before 2011.

Prevalence* of Self-Reported Obesity Among U.S.

Adults

by State and Territory, BRFSS, 2013 Summary

No state had a prevalence of obesity less than 20%.

7 states and the District of Columbia had a prevalence of obesity between 20% and <25%.

23 states had a prevalence of obesity between 25% and <30%.

18 states had a prevalence of obesity between 30% and <35%.

2 states (Mississippi and West Virginia) had a prevalence of obesity of 35% or greater.

The prevalence of obesity was 27.0% in Guam and 27.9% in Puerto Rico.+

http://www.cdc.gov/obesity/data/prevalence-maps.html

*Prevalence estimates reflect BRFSS methodological changes started in 2011. These estimates should not be compared to prevalence estimates before 2011.

+ Guam and Puerto Rico were the only US territories with obesity data available on the 2013 BRFSS.

Date of download: 9/24/2014 Copyright © 2014 American Medical

Association. All rights reserved.

From: Prevalence of Obesity and Trends in the Distribution of Body Mass Index Among US Adults, 1999-2010

JAMA. 2012;307(5):491-497. doi:10.1001/jama.2012.39

Values are weighted estimates.

Figure Legend:

35.5% 35.8%

Date of download: 9/24/2014 Copyright © 2014 American Medical

Association. All rights reserved.

From: Prevalence of Obesity and Trends in the Distribution of Body Mass Index Among US Adults, 1999-2010

JAMA. 2012;307(5):491-497. doi:10.1001/jama.2012.39

Figure Legend:

Prevalence of Self-Reported Obesity Among Hispanic Adults, by State, BRFSS, 2011-2013

Data not reported* 15%–<20% 20%–<25% 25%–<30% 30%– ≥35%

* Sample size <50 or the relative standard error (dividing the standard error by the prevalence) ≥ 30%.

Prevalence of Self-Reported Obesity Among Non-Hispanic Black Adults, by State, BRFSS, 2011-2013

Data not reported* 15%–<20% 20%–<25% 25%–<30% 30%–<35% ≥35%

* Sample size <50 or the relative standard error (dividing the standard error by the prevalence) ≥ 30%.

WHO Prevalence of Obesity 2008

COST OF OBESITY

Obesity Medicine

Epidemiology & Pathophysiology

Impact of Obesity Health Care Costs

Weight Loss Reduces Lifetime Healthcare Costs

Dall TM, et al. Am J Prev Med. 2011;40:338-344.

Projected Lifetime Healthcare Expenditures Obese Individuals <45 Years of Age

Cost offsets

+ $23

+ $930 + $1700

- $357

- $4080

- $8100

5% Weight Loss

for 2 Years

Total Benefit

$334

Permanent

5% Weight Loss

Total Benefit

$3150

Permanent

10% Weight Loss

Total Benefit

$6400

HOW DOES WEIGHT GAIN AFFECT HEALTH?

Obesity Medicine

Epidemiology & Pathophysiology

0

10

20

30

40

50

60

70

Relationship Between BMI and Percent Body Fat in Men and Women

Adapted from: Gallagher et al. Am J Clin Nutr 2000;72:694.

Bo

dy F

at (%

)

Body Mass Index (kg/m2)

0 10 30 40 60 20 50

Women

Men

Weight Gain and Body Fat

• Weight gain leads to excess body fat

• Visceral fat associated with higher risk for metabolic complications of excess weight

• Role of Waist circumference measurement

• BMI 25-35 kg/m2

• Men- > 40 inches

• Women > 35 inches

Relationship Between Visceral Adipose Tissue and Insulin Action

Am J Physiol .1997;273(2 pt 1):E425–E432.

18

16

14

12

10

8

6

4

2

0 1000 2000 3000 4000 5000

Visceral adipose tissue volume per unit surface area (mL/m2)

Glu

cose

dis

po

sal (

mg

/kg

LBM

/min

)

Women Men

BMI and Prevalence of Metabolic Disease by – NHANES 1999-2002

Under-

Weight

18.5-24.9 25-26.9 27-29.9 30-34.9 35-39.9 40 0

10

20

30

40

50

60

70 Diabetes Mellitus

Hypertension

Dyslipidemia

OVERALL <18.5

1.7

22.3 24

4.2

17.6

38.2

5.7

25.3

53.1

10.1

30.8

62.2

12.2

39.3

68

16.4

44

67.5

27.3

51.3

62.5

9

28.9

52.9

BMI

% o

f P

ati

en

ts

Normal Overweight Obese

Int J Clin Pract. 2007;61:737-747. Am J Med. 2009;122:S26-37.

Obesity-related Complications Obesity

NAFLD

Cardiovascular Disease

Dismotility/disability

GERD

Lung function

defects

Osteoarthritis

Sleep apnea

Urinary

incontinence

Pre-diabetic states

Hypertension Dyslipidemia

PCOS

Type 2 Diabetes

Cardiometabolic Biomechanical Other

GERD, gastroesophageal reflux disease; NAFLD, nonalcoholic fatty liver disease;

PCOS, polycystic ovary syndrome

Androgen

deficiency

Cancer

Gallbladder

disease

Psychological

disorders

Figure 3

Men and women. Adjusted for educational level, marital status, smoking, alcohol, physical activity, and BMI. WC cut

points were <90.0, 90.0 to 94.9, 95.0 to 99.9, 100.0 to 104.9, 105.0 to 109.9, and >110.0 cm for men and <70.0, 70.0 to

74.9, 75.0 to 79.9, 80.0 to 84.9, 85.0 to 89.9, and >90.0 cm for women. Mayo Clin Proc 2014; 89:335-345.

BMI, WC and Mortality HR and 95% CIs for WC (5-cm increments)

and all-cause mortality by BMI category.

Men and women.

Body Fat Distribution

• Gonadal steroids • Adolescent boys : Increased muscle

mass/Decreased fat mass

• Adolescent girls: Increased muscle/fat mass

• Visceral fat • Higher risk for metabolic/cardiovascular

complications

• Waist circumference measurement

• BMI’s 25-35 kg/m2

WHY ARE WE GETTING HEAVIER?

Obesity Medicine

Epidemiology & Pathophysiology

Factors Contributing to Weight Gain

• Genetic

• Physiologic

• Environmental

• Lifestyle

• Socioeconomic

• Cultural

Hard to change your genes

but not your jean size!

Genetic Factors • Single Gene Defects

• Leptin (ob gene)

• Signals the brain about stored body fat

• Decreases energy intake “adipostatic”

• Ob deficient mice: hyperphagia, insulin resistance, hyperinsulinemia, infertility

• Consanguineous families

• Leptin receptor gene

• Db/db mice

• Zucker rats

Genetic Factors

• Prader Willi

• Bardet Biedl

• Common obesity

• “Susceptibility” genes influenced by environmental factors

• Polymorphisms

Hereditary Factors

• BMI highly correlates within families

• Twin, adoptee, family studies

• Metabolic rate

• Thermic response to food

• Spontaneous physical activity

Physiologic Factors

• Metabolic rate

• Correlates with Fat Free Mass

Changes in Fat Free Mass lead to significant variations in energy expenditure

• Food intake

• Activity

Exercise

Non-Exercise Activity thermogenesis

Energy intake

Ingestion of:

Proteins

Fats

Carbohydrates

Energy expenditure

Physical activity

Meal-induced thermogenesis

Basal metabolic rate

Body Weight

Increase

Energy Homeostasis

Decrease Genetics

Environment

Behavior

Here is the Title Physiology Energy requirements

• Determinants of energy requirements

• Age Drops as we age

• Sex Higher for men than women

• Height Taller you are, the higher calorie needs

• Weight Heavier you are, the higher calorie needs

• Components of energy requirements • Basal metabolic rate

• Activity Exercise

NEAT (Non-Exercise Activity Thermogenesis)

(Calorie needs)

Here is the Title Estimated Calorie Requirements

• Harris Benedict Equation • Resting Energy Expenditure (REE) • Basal Metabolic Rate (BMR) • Men = 66 + 13.8 (kg) + 5(cm) – 6.8 (Age in years)

86.7 kg/170 cm/51 years 1766 kcal/d

• Women= 655 +9.5 (kg) + 1.9 (cm) – 4.7(Age in years) 86.7 kg/170cm/51 years 1562 kcal/d

• Activity Factor • 20-50% of estimated REE

Low (sedentary) Intermediate (Some regular exercise) High (Regular physical activity or physically demanding job)

Here is the Title

Estimated Calorie Requirements World Health Organization

• Estimate BMR • Men 18-30 = (0.0630 X (kg) + 2.8957) X 240 kcal/d • Men 31-60 = (0.0484 X (kg) + 3.6534 X 240 kcal/d • Women 18-30 = (0.0621 X (kg) + 2.0357) X 240 kcal/d

25 yrs/86.7 kg 1780 kcal/d

• Women 31-60 = (0.0342 X (kg) + 3.5377) X 240 kcal/d 40 yrs/86.7 kg 1560 kcal/d

• Determine Activity Factor (AF) Low 1.3 Intermediate 1.5 High 1.7

• Total energy expenditure= BMR X AF

Definition of Basal Metabolic Rate (BMR)

• The minimum energy consumption needed to sustain all cellular functions under steady state condition.

• All BMR measurements must meet the following conditions:

Completely rested (be lying down and fully awake) after awakening in the morning

Overnight fasted for at least 10 –12 hours

Under thermo-neutral (22–26ºC)

Free from emotional stress and familiar with the apparatus used

Terminology

• Residual BMR = Measured – Predicted BMR

• Predicted BMR = 674 + [15.5 x FFM (kg)]+[10.3 x fat mass (kg)]+[125 x sex (M=1, F=0)]-[4.4 x

age (y)]

Study design

Using residual BMR, we identified volunteers who were in the bottom and top 15th percentiles of BMR.

> 169 kcal/d

(top 15th percentile)

< -173 kcal/d

(bottom 15th percentile)

Total population Top 15th

percentile BMR

Bottom 15th percentile

BMR

P value

N 757 86 77

Male sex-no (%) 49 59 62 0.70

Age (years) 40 ± 17 39 ± 15 43 ± 17 0.16

Height (cm) 171.9 ± 9.8 174.0 ± 9.2 175.0 ± 9.7 0.53

Weight (kg) 80.2 ± 17.3 83.3 ± 18.4 86.4 ± 16.0 0.26

BMI (kg/m2) 27.1 ± 5.1 27.4 ± 5.2 28.3 ± 5.4 0.28

FFM (kg) 54.3 ± 12.4 56.9 ± 11.9 59.1 ± 11.2 0.23

Fat mass (kg) 25.5 ± 12.3 25.7 ± 12.1 27.1 ± 13.5 0.51

BMR (kcal/day) 1665 ± 322 2001 ± 317 1510 ± 222

Baseline characteristics of participants

with high and low BMR

491 kcal!

Physiologic Factors

• Obesity = Energy intake > Energy expenditure

• Not that simple

• Ignores multiple factors that modulate these two components

Effect of Diet Changes on Metabolic Rate

Each box encloses the data from the second and third quartiles and is bisected by a line at the

value for the median. The tips of vertical lines indicate the minimum and maximum values.

BMR, basal metabolic rate.

Dulloo AG, et al. Obes Rev. 2012;13(suppl 2):105-121.

Minnesota Experiment Healthy Men

Week 12 (n=32)

Week 24 (n=32)

Week 12 (n=32)

Week 16 (n=12)

Week 20 (n=12)

Semi-starvation Refeeding

Restricted Ad libitum Post-refeeding

hyperphagia

A

dju

ste

d B

MR

(%

co

ntr

ol p

eri

od

)

Physiologic Factors Differences in Metabolic Rates

Obese 50 y/o male, 180 cm initially at 250lbs, now at 212 lbs

• Weight loss 15%

• Decreased energy expenditure

• Decrease 15% of energy requirements

• HB equation – 15%=

• 1863 – 2235 kcal/day

Never Obese 50 y/o male , 180 cm at 212 lbs

• Stable

• Stable

• Stable

• HB equation=

• 2191-2630 kcal/day

This deficit can persist for 3-5 years

Obesity-related Impairments in Appetite Regulation & Energy Balance

Hormone Source Normal function Alteration

Cholecystokinin (CCK)

Duodenum Suppress appetite Levels decrease during dieting and weight loss

Glucose-dependent insulinotropic polypeptide (GIP)

Duodenum, jejunum

Energy storage Levels increase during dieting and weight loss

Ghrelin Gastric fundus Stimulate appetite, particularly for high-fat, high-sugar foods

Levels increase during dieting and weight loss

Glucagon-like peptide 1 (GLP-1)

Ileum Suppress appetite and increase satiety

Decreased functionality

Insulin Pancreas Regulate energy balance Signal satiety to brain

Insulin resistance in obese persons Reduced insulin levels after dieting

Leptin Adipocytes Regulate energy balance Suppress appetite

Levels decrease during weight loss

Peptide YY (PYY) Distal small intestine

Suppress appetite Levels decreased in obese persons

Sumithran P, Proietto J. Clin Sci (Lond). 2013;124:231-241.

Key Hormone Changes Associated with Weight Gain and Regain

Weight Gain and Food Supply

(A) The average adult body weight (Δ) as measured by the National Health and Nutrition Examination Survey. (B). Per capita U.S.

food availability unadjusted (○) and adjusted for wastage () according to the United States Department of Agriculture (USDA). The

solid curve represents the mathematical model prediction of average food intake change (dashed curves indicate±95% confidence

intervals). (C) Energy content of per capita U.S. food waste predicted using our mathematical model (solid curve, left axis). The right

axis plots the per capita annual mass of municipal solid food waste (). (D) Percentage of available food energy wasted as calculated

by previous USDA estimates () and predicted using our mathematical model (solid curve).

Hall KD et al. PLoS

One. 2009 Nov

25;4(11):e7940. doi:

10.1371/journal.pon

e.0007940

Changes in Diet and Lifestyle and Long Term Weight Gain in Men and Women

• > 120, 000 men and women • Participants gained an average of 3.35 lb every 4

years N E Med

Volume 364(25):2392-2404 June 23, 20

Mozaffarian D, et al. N Engl J Med. 364(25):2392-404

Relationships between changes in food and beverage consumption and weight changes every 4 years

Mozaffarian D et al. N Engl J

Med 2011;364:2392-2404

Relationships between Diet and Physical Activity and Weight Changes

Mozaffarian D et al.

N Engl J Med

2011;364:2392-2404

Environmental Factors that Increase Food Intake

Antecedents and mediators of food consumption volume

Wansink B. Annu. Rev. Nutr. 2004. 24:455–79

Appetite Regulation

Adapted from Neary NM, et al. Clin Endocrinol. 2004;60:153-160.

Noradrenergic

Endocannabinoid

Histamine and

Serotonin systems

White adipose tissue

Insulin

amylin

Nucleus of solitary tract

Paraventricular

nucleus

Lateral hypothalamus

Cerebral cortex

Sympathetic nervous

system

Brainstem nuclei

Hypothalamic arcuate nucleus neurons

Vagus nerve

Intestine

Stomach

PYY3-36

CCK

GLP-1

Ghrelin

obestatin

Leptin

NPY/AGRP

POMC Feeding

Gastric emptying

Metabolic rate?

Pancreas oxyntomodulin

Neural Signaling: Peripheral and Central Regulation of Energy Intake

AGRP, agouti-related peptide; CART, cocaine- and amphetamine-regulated transcript; CCK, cholecystokinin; GLP-1 glucagon-

like peptide 1; LH, lateral hypothalamus; NPY, neuropeptide Y; POMC, proopiomelanocortin; PVN, paraventricular nucleus;

PYY, peptide YY. Morton GJ, et al. Physiol Rev. 2011;91:389-411; Sumithran P, et al. Clin Sci (Lond). 2013;124:231-241.

Hypothalamus

Ghrelin

CCK PYY GLP-1

Leptin

Insulin

Amylin

Peripheral Signals

Arcuate nucleus Y1R Y5R

MC4R

MSH

AGRP

NPY

PVN, LH

Intake Higher cortical

centers

Intake

POMC/CART Neurons Anorexigenic = food intake • Stimulated by leptin and other

appetite-suppressing signals

NPY/AGRP Neurons Orexigenic = food intake • Stimulated by ghrelin • Inhibited by leptin

Serum Ghrelin After Gastric

Bypass Surgery

Cummings et al, NEJM, 2002

Factors in the Medical Realm

• Drug Induced Weight Gain • Psychotropic medications

• Seizure medications

• Diabetes medications

• Neuroendocrine mechanisms • Hypothalamic dysfunction

• Endocrine Disorders

• Infectious causes • Gut flora

Is Obesity a Disease?

• Condition of abnormal vital function involving any structure, part or system of an organism

• Disorder characterized by a recognizable set of signs and symptoms attributable to hereditary, infection, diet or environment

Obesity as A Disease

• American Medical Association

• August 2013 meeting

• Obesity officially recognized as a disease

• Against recommendation by the committee charged to study the subject

• AACE

• October 2012 Position Statement

NHLBI Classification of Weight, Waist Circumference & Disease Risk

Classification

BMI (kg/m2)

Disease Risk*

Men WC ≤40 in Women WC ≤35 in

Men WC >40 in Women WC >35 in

Underweight <18.5

Normal 18.5 – 24.9

Overweight 25.0-29.9 Increased High

Obesity Class I 30.0-34.9 High Very high

Obesity Class II 35.0-39.9 Very high Very high

Obesity Class III ≥40 Extremely high Extremely high

*Type 2 diabetes, hypertension, and cardiovascular disease.

BMI, body mass index; NHLBI, National Heart, Lung, and Blood Institute; WC, waist circumference

NHLBI Obesity Education Initiative. Obesity in adults. Available at: http://www.nhlbi.nih.gov/guidelines/obesity/prctgd_c.pdf.

Summary

• Obesity as defined by BMI of 30 kg/m2 continues to be an increasing health threat • Affects minority groups to a greater extent • Worldwide problem

• Obesity is a major contributor to rising health care costs • Currently in the management of its co-morbidities • There remain biases in coverage for obesity

treatments

• Many factors have contributed to the rising prevalence of obesity • Genetic, Hereditable, Physiologic, Environmental

Summary

• These factors represent obstacles the effective management of obesity

• Obesity meets the criteria for a disease but requires a multifaceted approach to management