REFERENCE CODE GDHCER022 PUBLICAT ION DATE AUGUST 2013 OVERWEIGHT AND OBESITY - EPIDEMIOLOGY FORECAST TO 2022

Similar documents
REFERENCE CODE GDHCER046 PUBLICAT ION DATE OCTOBER 2013 DIABETIC FOOT ULCERS - EPIDEMIOLOGY FORECAST TO 2022

REFERENCE CODE GDHCER052 PUBLICAT ION DATE NOVEMBER 2013 DIABETIC NEPHROPATHY - EPIDEMIOLOGY FORECAST TO 2022

REFERENCE CODE GDHCER043 PUBLICAT ION DATE NOVEMBER 2013 PARKINSON S DISEASE - EPIDEMIOLOGY FORECAST TO 2022

REFERENCE CODE GDHCER PUBLICAT ION DATE JULY 2014 ACUTE CORONARY SYNDROME (ACS) - EPIDEMIOLOGY FORECAST TO 2023

REFERENCE CODE GDHCER PUBLICAT ION DATE M AY 2015 GLAUCOMA EPIDEMIOLOGY FORECAST TO 2023

REFERENCE CODE GDHC282DFR PUBLICATION DATE OCTOBER 2013 BELVIQ (OBESITY) - FORECAST AND MARKET ANALYSIS TO 2022

REFERENCE CODE GDHC013POA PUBLICAT ION DATE DECEM BER 2013

REFERENCE CODE GDHC357DFR PUBLICAT ION DATE FEBRUARY 2014 CLOZARIL (SCHIZOPHRENIA) FORECAST AND MARKET ANALYSIS TO 2022

REFERENCE CODE GDHC361DFR PUBLICAT ION DATE FEBRUARY 2014 INVEGA (SCHIZOPHRENIA) FORECAST AND MARKET ANALYSIS TO 2022

REFERENCE CODE GDHC366DFR PUBLICAT ION DATE FEBRUARY 2014 CARIPRAZINE (SCHIZOPHRENIA) FORECAST AND MARKET ANALYSIS TO 2022

REFERENCE CODE GDHC386DFR PUBLICAT ION DATE M ARCH 2014 GARDASIL (PROPHYLACTIC HUMAN PAPILLOMAVIRUS VACCINES) - FORECAST AND MARKET ANALYSIS TO 2022

REFERENCE CODE GDHC199DFR PUBLICAT ION DATE JUNE 2013 XALKORI (NON-SMALL CELL LUNG CANCER) FORECAST AND MARKET ANALYSIS TO 2022

REFERENCE CODE GDHC518DFR PUBLICAT ION DATE DECEMBER 2014 LINZESS (IRRITABLE BOWEL SYNDROME) - FORECAST AND MARKET ANALYSIS TO 2023

REFERENCE CODE GDHC356DFR PUBLICAT ION DATE FEBRUARY 2014 SAPHRIS (SCHIZOPHRENIA) FORECAST AND MARKET ANALYSIS TO 2022

REFERENCE CODE GDHC200DFR PUBLICAT ION DATE JUNE 2013 AVASTIN (NON-SMALL CELL LUNG CANCER) FORECAST AND MARKET ANALYSIS TO 2022

REFERENCE CODE GDHC519DFR PUBLICAT ION DATE DECEMBER 2014 LOTRONEX (IRRITABLE BOWEL SYNDROME) FORECAST AND MARKET ANALYSIS TO 2023

REFERENCE CODE GDHC198DFR PUBLICAT ION DATE JUNE 2013 TARCEVA (NON-SMALL CELL LUNG CANCER) FORECAST AND MARKET ANALYSIS TO 2022

Kaletra (HIV) Forecast and Market Analysis to GDHC1051DFR/ Published January 2013

REFERENCE CODE GDHC196DFR PUBLICAT ION DATE JUNE 2013 ABRAXANE (NON-SMALL CELL LUNG CANCER) FORECAST AND MARKET ANALYSIS TO 2022

REFERENCE CODE GDHC420DFR PUBLICAT ION DATE M AY 2014 FETZIMA (MAJOR DEPRESSIVE DISORDER) - FORECAST AND MARKET ANALYSIS TO 2023

REFERENCE CODE GDHC525DFR PUBLICAT ION DATE DECEMBER 2014 TENAPANOR (IRRITABLE BOWEL SYNDROME) FORECAST AND MARKET ANALYSIS TO 2023

REFERENCE CODE GDHC397DFR PUBLICAT ION DATE M ARCH 2014 NOURIAST (PARKINSON S DISEASE) - FORECAST AND MARKET ANALYSIS TO 2022

REFERENCE CODE GDHC224CFR PUBLICAT ION DATE FEBRUARY 2014 SCHIZOPHRENIA US DRUG FORECAST AND MARKET ANALYSIS TO 2022

REFERENCE CODE GDHC207DFR PUBLICAT ION DATE JUNE 2013 GILOTRIF (NON-SMALL CELL LUNG CANCER) FORECAST AND MARKET ANALYSIS TO 2022

REFERENCE CODE GDHC521DFR PUBLICAT ION DATE DECEMBER 2014 ELUXADOLINE (IRRITABLE BOWEL SYNDROME) FORECAST AND MARKET ANALYSIS TO 2023

LUPUZOR (SYSTEMIC LUPUS ERYTHEMATOSUS AND LUPUS NEPHRITIS) - FORECAST AND MARKET ANALYSIS TO 2022

REFERENCE CODE GDHC422DFR PUBLICAT ION DATE M AY 2014 BRINTELLIX (MAJOR DEPRESSIVE DISORDER) - FORECAST AND MARKET ANALYSIS TO 2023

REFERENCE CODE GDHC398DFR PUBLICAT ION DATE M ARCH 2014 SAFINAMIDE (PARKINSON S DISEASE) - FORECAST AND MARKET ANALYSIS TO 2022

REFERENCE CODE GDHC423DFR PUBLICAT ION DATE M AY 2014 ABILIFY (MAJOR DEPRESSIVE DISORDER) - FORECAST AND MARKET ANALYSIS TO 2023

REFERENCE CODE GDHC395DFR PUBLICAT ION DATE M ARCH 2014 APOKYN (PARKINSON S DISEASE) - FORECAST AND MARKET ANALYSIS TO 2022

REFERENCE CODE GDHC426DFR PUBLICAT ION DATE M AY 2014 CARIPRAZINE (MAJOR DEPRESSIVE DISORDER) - FORECAST AND MARKET ANALYSIS TO 2023

REFERENCE CODE GDHC401DFR PUBLICAT ION DATE M ARCH 2014 RYTARY/IPX066 (PARKINSON S DISEASE) - FORECAST AND MARKET ANALYSIS TO 2022

REFERENCE CODE GDHC391DFR PUBLICAT ION DATE M ARCH 2014 DUODOPA (PARKINSON S DISEASE) - FORECAST AND MARKET ANALYSIS TO 2022

REFERENCE CODE GDHC425DFR PUBLICAT ION DATE M AY 2014 BREXPIPRAZOLE (MAJOR DEPRESSIVE DISORDER) - FORECAST AND MARKET ANALYSIS TO 2023

REFERENCE CODE GDHC465DFR PUBLICAT ION DATE SEPTEMBER 2014 KADCYLA (HER2-POSITIVE BREAST CANCER) - FORECAST AND MARKET ANALYSIS TO 2023

Synribo (Chronic Myeloid Leukemia)

REFERENCE CODE GDHC1161DFR PUBLICAT ION DATE SEPTEMBER 2013 MENOMUNE (MENINGOCOCCAL VACCINES) - FORECAST AND MARKET ANALYSIS TO 2022

Rituxan (Rheumatoid Arthritis)

Orencia (Rheumatoid Arthritis)

REFERENCE CODE GDHC378DFR PUBLICAT ION DATE M ARCH 2014 BOTOX (MIGRAINE) - FORECAST AND MARKET ANALYSIS TO 2023

REFERENCE CODE GDHC1155DFR PUBLICAT ION DATE SEPTEMBER 2013 NIMENRIX (MENINGOCOCCAL VACCINES) FORECAST AND MARKET ANALYSIS TO 2022

REFERENCE CODE GDHC392DFR PUBLICATION DATE M ARCH 2014 STALEVO/COMTAN (PARKINSON S DISEASE) - FORECAST AND MARKET ANALYSIS TO 2022

Actemra (Rheumatoid Arthritis)

REFERENCE CODE GDHC1042FPR PUBLICAT ION DATE DECEMBER 2014 IRRITABLE BOWEL SYNDROME CURRENT AND FUTURE PLAYERS

REFERENCE CODE GDHC220DFR PUBLICAT ION DATE JULY 2013 JANUVIA (TYPE 2 DIABETES) - FORECAST AND MARKET ANALYSIS TO 2022

REFERENCE CODE GDHC109PIDR PUBLICAT ION DATE MAY 2015 FIBROMYALGIA GLOBAL DRUG FORECAST AND MARKET ANALYSIS TO 2023

REFERENCE CODE GDHC1087DFR PUBLICATION DATE JUNE 2013

Chronic Myeloid Leukemia (CML)

Diquas (Dry Eye Syndrome)

REFERENCE CODE GDHC238DFR PUBLICAT ION DATE JULY 2013 EMPAGLIFLOZIN (TYPE 2 DIABETES) - FORECAST AND MARKET ANALYSIS TO 2022

REFERENCE CODE GDHC294DFR PUBLICATION DATE NOVEMBER 2013 PROTOPIC (ATOPIC DERMATITIS) FORECAST AND MARKET ANALYSIS TO 2022

REFERENCE CODE GDHC476DFR PUBLICAT ION DATE NOVEMBER 2014 CYRAMZA (COLORECTAL CANCER) FORECAST AND MARKET ANALYSIS TO 2023

REFERENCE CODE GDHC472DFR PUBLICAT ION DATE NOVEM BER 2014 STIVARGA (COLORECTAL CANCER) FORECAST AND MARKET ANALYSIS TO 2023

REFERENCE CODE GDHC1170DFR PUBLICATION DATE M AY 2013

REFERENCE CODE GDHC471DFR PUBLICAT ION DATE NOVEM BER 2014 VECTIBIX (COLORECTAL CANCER) FORECAST AND MARKET ANALYSIS TO 2023

REFERENCE CODE GDHC1174DFR PUBLICATION DATE M AY 2013

REFERENCE CODE GDHC1032FPR PUBLICAT ION DATE M ARCH 2014 PROPHYLACTIC HUMAN PAPILLOMAVIRUS VACCINES - CURRENT AND FUTURE PLAYERS

Cyclokat (Dry Eye Syndrome)

REFERENCE CODE GDHC241DFR PUBLICAT ION DATE JULY 2013 FASIGLIFAM (TYPE 2 DIABETES) - FORECAST AND MARKET ANALYSIS TO 2022

Dry Eye Syndrome. US Drug Forecast and Market Analysis to GDHC1115CFR / Published May 2013

REFERENCE CODE GDHC1062CFR PUBLICATION DATE JUNE 2013 CHRONIC HEART FAILURE - JAPAN DRUG FORECAST AND MARKET ANALYSIS TO 2022

REFERENCE CODE GDHC233DFR PUBLICAT ION DATE JULY 2013 ALBIGLUTIDE (TYPE 2 DIABETES) - FORECAST AND MARKET ANALYSIS TO 2022

PegIntron (Hepatitis C Virus) Forecast and Market Analysis to GDHC1143DFR / Published May 2013

Dry Eye Syndrome - Current and Future Players. GDHC1016FPR / Published May 2013

REFERENCE CODE GDHC296DFR PUBLICATION DATE NOVEMBER 2013 DUPILUMAB (ATOPIC DERMATITIS) FORECAST AND MARKET ANALYSIS TO 2022

REFERENCE CODE GDHC295DFR PUBLICATION DATE NOVEMBER 2013 ELIDEL (ATOPIC DERMATITIS) FORECAST AND MARKET ANALYSIS TO 2022

Keppra (Epilepsy) Forecast and Market Analysis to Reference Code: GDHC1061DFR Publication Date: February 2013

REFERENCE CODE GDHC317DFR PUBLICAT ION DATE DECEMBER 2013 LUCENTIS (MICROVASCULAR COMPLICATIONS OF DIABETES) - FORECAST AND MARKET ANALYSIS TO 2022

REFERENCE CODE GDHC1114CFR PUBLICATION DATE M AY 2013

REFERENCE CODE GDHC321DFR PUBLICAT ION DATE DECEMBER 2013 ATRASENTAN (MICROVASCULAR COMPLICATIONS OF DIABETES) - FORECAST AND MARKET ANALYSIS TO 2022

Sofosbuvir and Sofosbuvir/Ledipasvir (Hepatitis C Virus) Forecast and Market Analysis to GDHC1150DFR / Published May 2013

Lamictal (Epilepsy) Forecast and Market Analysis to Reference Code: GDHC1062DFR Publication Date: February 2013

REFERENCE CODE GDHC407DFR PUBLICAT ION DATE APRIL 2014 QUTENZA (NEUROPATHIC PAIN) - FORECAST AND MARKET ANALYSIS TO 2022

REFERENCE CODE GDHC406DFR PUBLICAT ION DATE APRIL 2014 LIDODERM/VERSATIS (NEUROPATHIC PAIN) - FORECAST AND MARKET ANALYSIS TO 2022

REFERENCE CODE GDHC334DFR PUBLICAT ION DATE J ANU ARY 2014 ENGERIX-B (PROPHYLACTIC HEPATITIS B VIRUS VACCINES) - FORECAST AND MARKET ANALYSIS TO 2022

REFERENCE CODE GDHC1013FPR PUBLICAT ION DATE AUGUST 2013 MENINGOCOCCAL VACCINES - CURRENT AND FUTURE PLAYERS

REFERENCE CODE GDHC237CFR PUBLICAT ION DATE M ARCH 2014 PARKINSON S DISEASE - JAPAN DRUG FORECAST AND MARKET ANALYSIS TO 2022

REFERENCE CODE GDHC1033FPR PUBLICAT ION DATE M ARCH 2014 PARKINSON S DISEASE - CURRENT AND FUTURE PLAYERS

REFERENCE CODE GDHC235CFR PUBLICAT ION DATE M ARCH 2014 PARKINSON S DISEASE - US DRUG FORECAST AND MARKET ANALYSIS TO 2022

REFERENCE CODE GDHC319DFR PUBLICAT ION DATE DECEMBER 2013 EYLEA (MICROVASCULAR COMPLICATIONS OF DIABETES) - FORECAST AND MARKET ANALYSIS TO 2022

REFERENCE CODE GDHC509DFR PUBLICAT ION DATE DECEMBER 2014 MAVRILIMUMAB (RHEUMATOID ARTHRITIS) FORECAST AND MARKET ANALYSIS TO 2023

EU5 Bariatric Surgery Procedures Outlook to 2020

REFERENCE CODE GDHC501DFR PUBLICAT ION DATE DECEMBER 2014 XELJANZ (TOFACITINIB) (RHEUMATOID ARTHRITIS) - FORECAST AND MARKET ANALYSIS TO 2023

Cytomegalovirus (CMV) Infections - Pipeline Assessment and Market Forecasts to 2019

REFERENCE CODE GDHC497DFR PUBLICAT ION DATE DECEMBER 2014 ORENCIA (ABATACEPT) (RHEUMATOID ARTHRITIS) - FORECAST AND MARKET ANALYSIS TO 2023

REFERENCE CODE GDHC482DFR PUBLICAT ION DATE OCTOBER 2014 EYLEA (MACULAR EDEMA AND MACULAR DEGENERATION) - FORECAST AND MARKET ANALYSIS TO 2023

REFERENCE CODE GDHC239CFR PUBLICAT ION DATE APRIL 2014 NEUROPATHIC PAIN - US DRUG FORECAST AND MARKET ANALYSIS TO 2022

NONALCOHOLIC STEATOHEPATITIS (NASH) - OPPORTUNITY ANALYSIS AND FORECASTS TO EVENT-DRIVEN UPDATE

REFERENCE CODE GDHC183CFR PUBLICAT ION DATE NOVEM BER 2013 ATOPIC DERMATITIS US DRUG FORECAST AND MARKET ANALYSIS TO 2022

REFERENCE CODE GDME1086CFR PUBLICAT ION DATE FEBRUARY 2014 BIOPSY DEVICES APAC ANALYSIS AND MARKET FORECASTS

BRIC Transurethral Resection of the Prostate (TURP) Procedures Outlook to 2020

REFERENCE CODE GDHC496DFR PUBLICAT ION DATE DECEMBER 2014 CIMZIA (CERTOLIZUMAB PEGOL) (RHEUMATOID ARTHRITIS) - FORECAST AND MARKET ANALYSIS TO 2023

REFERENCE CODE GDME0188M AR PUBLICATION DATE FEBRUARY 2014 BIOPSY DEVICES - GLOBAL ANALYSIS AND MARKET FORECASTS

Asia-Pacific Bariatric Surgery Devices Market Outlook to 2020

SAMPLE. Sterilization and Disinfectant Equipment Market Outlook in BRICS (Brazil, Russia, India, China, South Africa) to 2018

REFERENCE CODE GDHC502DFR PUBLICAT ION DATE DECEMBER 2014 IGURATIMOD/T-614 (RHEUMATOID ARTHRITIS) - FORECAST AND MARKET ANALYSIS TO 2023

REFERENCE CODE GDHC68PIDR PUBLICATION DATE JANUARY 2014 PROPHYLACTIC HEPATITIS B VIRUS VACCINES - GLOBAL DRUG FORECAST AND MARKET ANALYSIS TO 2022

REFERENCE CODE GDHC504DFR PUBLICAT ION DATE DECEMBER 2014 SARILUMAB (RHEUMATOID ARTHRITIS) FORECAST AND MARKET ANALYSIS TO 2023

Diagnostic Cardiac Biomarkers for Acute Coronary Syndromes

Transcription:

REFERENCE CODE GDHCER022 PUBLICAT ION DATE AUGUST 2013 OVERWEIGHT AND OBESITY -

Executive Summary Obesity is an escalating global public health problem that has reached pandemic proportions. It is caused by a combination of excessive caloric intake and physical inactivity, which, in turn, leads to excessive fat accumulation in the body, negatively impacting health. Obesity is the major cause of type 2 diabetes, coronary heart disease, and ischemic stroke, which are increasing globally (Larson and Wolk, 2006). The World Health Organization (WHO) estimates that worldwide, 2.8 million people die each year due to obesity and its associated comorbidities (WHO, 2013a). Moreover, 35.8 million (2.3%) of global disabilityadjusted life years (DALYs) are caused by overweight/obesity (WHO, 2013d). Globally, in 2008, 35% of adults ages 20 years and older were overweight, as defined by a body mass index (BMI) of 25 kg/m 2 (includes all overweight and obese), and 11% were obese (BMI 30 kg/m 2 ) (WHO, 2013a; WHO, 2013c; WHO, 2013d). During 1980 2008, the obesity prevalence almost doubled globally. In 1980, only 5% of men and 8% of women over the age of 20 years were obese, and in 2008, these proportions almost doubled to 10% for men and 14% for women, resulting in an estimated 205 million and 297 million prevalent cases of obesity in men and women, respectively (WHO, 2013d). This report provides an overview of the risk factors, comorbidities, and the global trends for overweight and obesity in the nine major markets (9MM) (US, France, Germany, Italy, Spain, UK, Japan, Brazil, and Canada). The report also includes a 10-year epidemiology forecast of the prevalent cases of overweight, obesity, obesity class I, obesity class II, and obesity class III segmented by sex and age. In addition, the report includes a 10-year forecast of the prevalent cases of obesity-associated comorbidities, such as diagnosed diabetes, diagnosed hypertension, and dyslipidemia, among adults with overweight/obesity in some of these markets. To forecast the prevalent cases of overweight, obesity, obesity class I, obesity class II, and obesity class III segmented by sex and age in these major markets, GlobalData epidemiologists used longitudinal historical data obtained from country-specific, national-level studies using the uniform diagnostic criteria specified by the WHO for overweight (BMI = 25.00 29.99 kg/m 2 ), obesity (BMI = 30.00 kg/m 2 ), obesity class I (BMI = 30.00 34.99 kg/m 2 ), obesity class II (BMI = 35.00 39.99 kg/m 2 ), and obesity class III (BMI = 40.00 kg/m 2 ), and applied regression methods to forecast the prevalent cases (WHO, 2013c). GlobalData epidemiologists used country-specific national or regional studies that mirror the national population to develop a forecast for the hypertension, dyslipidemia, and type 2 diabetes comorbidities in selected markets. 2

Executive Summary As shown in the below figures, GlobalData epidemiologists forecast that the number of prevalent cases of overweight in the 9MM will grow by 8.70% during the forecast period, from 250.05 million cases in 2012 to 271.86 million cases by 2022. Compared with overweight, GlobalData epidemiologists forecast a substantial growth in the projected number of prevalent cases of obesity in the 9MM, with a 27.5% increase during the forecast period, from 167.39 million cases in 2012 to 213.34 million cases in 2022. Throughout the forecast period, the US will have the most prevalent cases of overweight and obesity, with 80.75 million cases of overweight and 112.78 million cases of obesity by 2022, followed by Brazil, with 63.83 million cases of overweight and 26.34 million cases of obesity. 9MM, Prevalent Cases of Overweight, Ages 18 Years, Both Sexes, N (Millions), 2012 and 2022 9MM 7MM 5EU US Brazil Japan Germany UK Italy France Spain Canada 18.50 18.59 16.64 17.59 16.12 17.38 14.38 17.19 9.54 9.37 24.25 26.37 23.38 20.78 48.56 63.83 89.02 91.53 78.69 80.75 191.96 198.65 250.05 271.86 0 50 100 150 200 250 300 Prevalent Cases of Overweight (N=Millions) 2012 2022 Source: GlobalData; CCHS, 2004; Charles et al., 2008; CHMS, 2010; CHMS, 2012; Flegal et al., 2010; Flegal et al., 2012; Gallus et al., 2006; Gallus et al., 2013; Gigante et al., 2011; Hauner et al., 2008; HSE, 2011; INE, 2013a; INE, 2013b; INE, 2013c; Monteiro et al., 2007; Ogden et al., 2006; Tanaka and Kokubo, 2005; WHO, 2011; WHO, 2013b; Yoshiike et al., 2002. Note: 5EU = France, Germany, Italy, Spain, and UK; 7MM = US, 5EU, and Japan; 9MM = 7MM, Brazil, and Canada 9MM, Prevalent Cases of Obesity, Ages 18 Years, Both Sexes, N (Millions), 2012 and 2022 9MM 7MM US 5EU Brazil Germany UK France Canada Spain Italy Japan 8.23 11.41 7.62 9.90 6.65 9.22 4.77 5.15 3.66 4.00 19.17 26.34 16.55 18.85 12.93 15.69 49.13 60.32 87.80 112.78 140.60 167.39 177.10 213.34 0 50 100 150 200 250 Prevalent Cases of Obesity (N=Millions) 2012 2022 Source: GlobalData; CCHS, 2004; Charles et al., 2008; CHMS, 2010; CHMS, 2012; Flegal et al., 2010; Flegal et al., 2012; Gallus et al., 2006; Gallus et al., 2013; Gigante et al., 2011; Hauner et al., 2008; HSE, 2011; INE, 2013a; INE, 2013b; INE, 2013c; Monteiro et al., 2007; Tanaka and Kokubo, 2005; WHO, 2011; WHO, 2013b; Yoshiike et al., 2002. Note: 5EU = France, Germany, Italy, Spain, and UK; 7MM = US, 5EU, and Japan; 9MM = 7MM, Brazil, and Canada The major drivers of the substantial increase in the projected prevalence and prevalent cases of overweight and obesity in the 9MM is both an increased adoption of a westernized lifestyle and an increase in the prevalence of obesity risk factors. As modern lifestyles typically include risk factors such as a sedentary lifestyle and physical inactivity combined with high caloric intake, it will be difficult for public health organizations and policymakers to aim for effective control measures at a population level to curtail this fast-growing epidemic. As a result, GlobalData epidemiologists predict that the obesity epidemic and its associated comorbidities will continue to increase, making them a significant threat to public health. 3

1 1... 4 1.1 List of Tables... 8 1.2 List of Figures... 10 2 Introduction... 12 2.1 Catalyst... 12 2.2 Related Reports... 13 2.3 Upcoming Reports... 13 3 Epidemiology... 14 3.1 Disease Overview... 14 3.2 Risk Factors and Comorbidities... 15 3.2.1 Family history is a strong predictor of obesity... 15 3.2.2 Physical inactivity is an independent predictor of obesity... 16 3.2.3 Excessive caloric intake doubles the risk for obesity... 17 3.2.4 Hypertension is as high as 42% in obese adults... 18 3.2.5 Dyslipidemia and type 2 diabetes are common comorbidities in obese patients... 19 3.3 Global Trends... 21 3.3.1 US... 22 3.3.2 5EU... 24 3.3.3 Japan... 30 3.3.4 Brazil... 31 3.3.5 Canada... 33 3.4 Forecast Methodology... 34 4

3.4.1 Sources Used... 41 3.4.2 Forecast Assumptions and Methods: Prevalent Cases of Overweight, Obesity, Obesity by Class, and Comorbidities... 48 3.4.3 Sources Not Used... 65 3.5 Epidemiology Forecast of Overweight (2012 2022)... 65 3.5.1 Prevalent Cases of Overweight... 65 3.5.2 Age-Specific Prevalent Cases of Overweight... 67 3.5.3 Sex-Specific Prevalent Cases of Overweight... 69 3.5.4 Age-Standardized Prevalence of Overweight... 72 3.6 Epidemiology Forecast of Obesity (2012 2022)... 73 3.6.1 Prevalent Cases of Obesity... 73 3.6.2 Age-Specific Prevalent Cases of Obesity... 75 3.6.3 Sex-Specific Prevalent Cases of Obesity... 77 3.6.4 Age-Standardized Prevalence of Obesity... 78 3.7 Epidemiology Forecast of Obesity Class I (2012 2022)... 79 3.7.1 Prevalent Cases of Obesity Class I... 79 3.7.2 Age-Specific Prevalent Cases of Obesity Class I... 81 3.7.3 Sex-Specific Prevalent Cases of Obesity Class I... 83 3.7.4 Age-Standardized Prevalence of Obesity Class I... 85 3.8 Epidemiology Forecast of Obesity Class II (2012 2022)... 87 3.8.1 Prevalent Cases of Obesity Class II... 87 3.8.2 Age-Specific Prevalent Cases of Obesity Class II... 89 3.8.3 Sex-Specific Prevalent Cases of Obesity Class II... 91 5

3.8.4 Age-Standardized Prevalence of Obesity Class II... 93 3.9 Epidemiology Forecast of Obesity Class III (2012 2022)... 95 3.9.1 Prevalent Cases of Obesity Class III... 95 3.9.2 Age-Specific Prevalent Cases of Obesity Class III... 97 3.9.3 Sex-Specific Prevalent Cases of Obesity Class III... 99 3.9.4 Age-Standardized Prevalence of Obesity Class III... 101 3.10 Epidemiology Forecast of Comorbidities among Adults with Overweight/Obesity (2012 and 2022)... 103 3.10.1 Prevalent Cases of Diagnosed Diabetes among Adults with Overweight/Obesity... 103 3.10.2 Prevalent Cases of Diagnosed Hypertension in Adults with Overweight/Obesity... 106 3.10.3 Prevalent Cases of Dyslipidemia among Adults with Overweight/Obesity... 108 3.11 Discussion... 111 3.11.1 Conclusions on Epidemiological Trends... 111 3.11.2 Limitations of the Analysis... 112 3.11.3 Strengths of the Analysis... 113 4 Appendix... 114 4.1 Bibliography... 114 4.2 About the Authors... 120 4.2.1 Epidemiologists... 120 4.2.2 Reviewers... 120 4.2.3 Global Director of Epidemiology and Health Policy... 121 4.2.4 Global Head of Healthcare... 122 4.3 About GlobalData... 123 6

4.4 About EpiCast... 123 4.5 Disclaimer... 124 7

1.1 List of Tables Table 1: The WHO Classification System of Adult Overweight and Obesity According to BMI... 14 Table 2: Risk Factors and Comorbidities of Obesity... 15 Table 3: 9MM, Age-Adjusted and Crude Prevalence (%) of Obesity, by Sex, Ages 20 Years, 2008... 22 Table 4: JASSO and WHO Classifications of Obesity... 30 Table 5: Sources of Epidemiological Data Used for Forecasting the Prevalent Cases of Overweight... 35 Table 6: Sources of Epidemiological Data Used for Forecasting the Prevalent Cases of Obesity... 36 Table 7: Sources of Epidemiological Data Used for Forecasting the Prevalent Cases of Obesity Class I, Class II, and Class III... 38 Table 8: Sources of Epidemiological Data Used for Forecasting the Prevalent Cases of Comorbidities in Overweight/Obese... 40 Table 9: 9MM, Prevalent Cases of Overweight, Ages 18 Years, Both Sexes, N (Millions), 2012 2022... 66 Table 10: 9MM, Prevalent Cases of Overweight, By Age, Both Sexes, N (Millions), Row (%), 2012... 68 Table 11: 9MM, Prevalent Cases of Overweight, Ages 18 Years, By Sex, N (Millions), Row (%), 2012... 70 Table 12: 9MM, Prevalent Cases of Obesity, Ages 18 Years, Both Sexes, N (Millions), 2012 2022... 74 Table 13: 9MM, Prevalent Cases of Obesity, By Age, Both Sexes, N (Millions), Row (%), 2012... 76 Table 14: 9MM, Prevalent Cases of Obesity, Ages 18 Years, by Sex, N (Millions), Row (%), 2012... 77 Table 15: 9MM, Prevalent Cases of Obesity Class I, Ages 18 Years, Both Sexes, N (Millions), 2012 2022... 80 Table 16: 9MM, Prevalent Cases of Obesity Class I, by Age, Both Sexes, N (Millions), Row (%), 2012... 82 Table 17: 9MM, Prevalent Cases of Obesity Class I, Ages 18 Years, By Sex, N (Millions), Row (%), 2012. 84 Table 18: 9MM, Prevalent Cases of Obesity Class II, Ages 18 Years, Both Sexes, N (Millions), 2012 2022... 88 Table 19: 9MM, Prevalent Cases of Obesity Class II, By Age, Both Sexes, N (Millions), Row (%), 2012... 90 Table 20: 9MM, Prevalent Cases of Obesity Class II, Ages 18 Years, By Sex, N (Millions), Row (%), 2012... 92 8

Table 21: 9MM, Prevalent Cases of Obesity Class III, Ages 18 Years, Both Sexes, N (Millions), 2012 2022... 96 Table 22: 9MM, Prevalent Cases of Obesity Class III, By Age, Both Sexes, N (Millions), Row (%), 2012... 98 Table 23: 9MM, Prevalent Cases of Obesity Class III, Ages 18 Years, By Sex, N (Millions), Row (%), 2012... 100 Table 24: 5MM*, Prevalent Cases of Diagnosed Diabetes among Adults with Overweight/Obesity, Both Sexes, N (Millions), 2012 and 2022... 104 Table 25: 6MM*, Prevalent Cases of Diagnosed Hypertension among Adults with Overweight/Obesity, Both Sexes, N (Millions), 2012 and 2022... 107 Table 26: 4MM, Prevalent Cases of Dyslipidemia* among Adults with Overweight/Obesity, Both Sexes, N (Millions), 2012 and 2022... 109 9

1.2 List of Figures Figure 1: US, Overweight and Obesity Age-Adjusted Prevalence (%), Ages 20 74 Years, Men, 1960 2010... 23 Figure 2: US, Overweight and Obesity Age-Adjusted Prevalence (%), Ages 20 74 Years, Women, 1960 2010... 23 Figure 3: France, Overweight and Obesity Prevalence (%), Ages 15 Years, Men, 1997 2006... 25 Figure 4: France, Overweight and Obesity Prevalence (%), Ages 15 Years, Women, 1997 2006... 25 Figure 5: Italy, Overweight and Obesity Prevalence (%), Ages 18, Men, 1983 2010... 27 Figure 6: Italy, Overweight and Obesity Prevalence (%), Ages 18, Men, 1983 2010... 27 Figure 7: UK, Overweight and Obesity Prevalence (%), Ages 16 Years, Men, 1993 2011... 29 Figure 8: UK, Overweight and Obesity Prevalence (%), Ages 16 Years, Women, 1993 2011... 29 Figure 9: Japan, Obesity Prevalence (%), Ages 20 Years, By Sex, 1976 2006... 31 Figure 10: Brazil, Overweight and Obesity Prevalence (%), Ages 20 Years, Men, 1975 2003... 32 Figure 11: Brazil, Overweight and Obesity Prevalence (%), Ages 20 Years, Women, 1975 2003... 32 Figure 12: Canada, Obesity Prevalence (%), Ages 18 Years, Both Sexes, 1978 2008... 34 Figure 13: 9MM, Prevalent Cases of Overweight, Ages 18 Years, Both Sexes, N (Millions), 2012 2022... 67 Figure 14: 9MM, Prevalent Cases of Overweight, by Age, Both Sexes, N (Millions), 2012... 69 Figure 15: 9MM, Prevalent Cases of Overweight, Ages 18 Years, by Sex, N (Millions), 2012... 71 Figure 16: 9MM, Overweight Age-Standardized Prevalence (%), Ages 18 Years, By Sex, 2012... 73 Figure 17: 9MM, Prevalent Cases of Obesity, Ages 18 Years, Both Sexes, N (Millions), 2012 2022... 75 Figure 18: 9MM, Prevalent Cases of Obesity, By Age, Both Sexes, N (Millions), 2012... 76 Figure 19: 9MM, Prevalent Cases of Obesity, Ages 18 Years, by Sex, N (Millions), 2012... 78 Figure 20: 9MM, Obesity Age-Standardized Prevalence (%), Ages 18 Years, By Sex, 2012... 79 Figure 21: 9MM*, Prevalent Cases of Obesity Class I, Ages 18 Years, Both Sexes, N (Millions), 2012 2022... 81 10

Figure 22: 9MM*, Prevalent Cases of Obesity Class I, By Age, Both Sexes, N (Millions), 2012... 83 Figure 23: 9MM*, Prevalent Cases of Obesity Class I, Ages 18 Years, by Sex, N (Millions), 2012... 85 Figure 24: 9MM*, Obesity Class I Age-Standardized Prevalence (%), Ages 18 Years, by Sex, 2012... 86 Figure 25: 9MM*, Prevalent Cases of Obesity Class II, Ages 18 Years, Both Sexes, N (Millions), 2012 2022... 89 Figure 26: 9MM*, Prevalent Cases of Obesity Class II, By Age, Both Sexes, N (Millions), 2012... 91 Figure 27: 9MM*, Prevalent Cases of Obesity Class II, Ages 18 Years, by Sex, N (Millions), 2012... 93 Figure 28: 9MM*, Age-Standardized Prevalence (%) of Obesity Class II, Ages 18 Years, By Sex, 2012... 94 Figure 29: 9MM*, Prevalent Cases of Obesity Class III, Ages 18 Years, Both Sexes, N (Millions), 2012 2022... 97 Figure 30: 9MM*, Prevalent Cases of Obesity Class III, By Age, Both Sexes, N (Millions), 2012... 99 Figure 31: 9MM*, Prevalent Cases of Obesity Class III, Ages 18 Years, By Sex, N (Millions), 2012... 101 Figure 32: 9MM*, Obesity Class III Age-Standardized Prevalence (%), Ages 18 Years, By Sex, 2012... 102 Figure 33: 5MM*, Prevalent Cases of Diagnosed Diabetes among Adults with Overweight/Obesity, Both Sexes, N (Millions), 2012... 105 Figure 34: 6MM*, Prevalent Cases of Diagnosed Hypertension among Adults with Overweight/Obesity, Both Sexes, N (Millions), 2012... 108 Figure 35: 4MM*, Prevalent Cases of Dyslipidemia** among Adults with Overweight/Obesity, Both Sexes, N (Millions), 2012... 110 11

Introduction 2 Introduction 2.1 Catalyst Overweight and obesity are diseases characterized by abnormal or excessive fat accumulation in the body, which can increase the likelihood of developing type 2 diabetes and cardiovascular diseases (Larson and Wolk, 2006; WHO, 2013a). The World Health Organization (WHO) classifies overweight and obesity by body mass index (BMI). A BMI of 25 kg/m 2 is considered overweight, and a BMI of 30 kg/m 2 is considered to be obese (WHO, 2013c). Obesity is an escalating public health problem with an increasing prevalence worldwide, and it has become a well-known threat to public health (WHO, 2013d). To provide a thorough description of the overweight and obese (all obese, class I obesity, class II obesity, class III obesity) patient population in each country, GlobalData epidemiologists segmented the overweight and obesity prevalent cases by sex, age (in five-year increments, beginning at age 18 years and ending at 85 years) in the nine major markets (9MM) (US, France, Germany, Italy, Spain, UK, Japan, Brazil, and Canada). GlobalData epidemiologists forecast that there were 250.05 million prevalent cases of overweight adults in the 9MM in 2012, which will increase to 271.86 million cases in 2022, increasing at an Annual Growth Rate (AGR) of 0.86%. GlobalData epidemiologists forecast that there were 167.39 million prevalent cases of obesity in the 9MM in 2012, which will increase to 213.34 million cases in 2022, increasing at an AGR of 2.75%. While the trend in the prevalent cases of overweight remains almost stable for most of the 9MM during the forecast period, a substantial growth in the prevalent cases of obesity is seen in most of the markets. Approximately 57% of the 250.05 million prevalent cases of overweight adults in the 9MM in 2012 were in men. Approximately 52% of the 167.39 million prevalent cases of obese adults in the 9MM in 2012 were in women. 12

Appendix 4.3 About GlobalData GlobalData is a leading global provider of business intelligence in the Healthcare industry. GlobalData provides its clients with up-to-date information and analysis on the latest developments in drug research, disease analysis, and clinical research and development. Our integrated business intelligence solutions include a range of interactive online databases, analytical tools, reports and forecasts. Our analysis is supported by a 24/7 client support and analyst team. GlobalData has offices in New York, Boston, London, India and Singapore. 4.4 About EpiCast EpiCast is a series of premier epidemiology reports written and developed by Masters and PhD level epidemiologists. EpiCast Reports are in-depth, high quality, transparent and market-driven, providing expert analysis of epidemiological trends and forecasting of patient populations for major markets. Specifically, the reports identify disease trends over a 10-year forecast period in six to seven major markets (US, France, Germany, Italy, Spain, UK, Japan). Additional countries, such as Canada, Brazil, India and China, are covered in these reports if their markets are highly relevant. 123

Appendix 4.5 Disclaimer All Rights Reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form by any means, electronic, mechanical, photocopying, recording or otherwise, without the prior permission of the publisher, GlobalData. 124