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Figure 1.
Lifetime Risk of Cardiovascular Disease (CVD) Morbidity and Mortality Among Middle-aged Individuals
Lifetime Risk of Cardiovascular Disease (CVD) Morbidity and Mortality Among Middle-aged Individuals

Remaining cumulative lifetime risk estimates for total CVD events (adjusted for competing risk of noncardiovascular death) in middle-aged (index age, 40-59 years) men (A) and women (B) stratified by body mass index groups: underweight, normal, overweight, obese, and morbidly obese. Lifetime risks for total cardiovascular disease exceeded 30% for men and women in all body mass index groups. Participants in higher body mass index strata had higher lifetime risks for total cardiovascular disease through age 95 years.

Figure 2.
Years Lived Free of and With Cardiovascular Disease (CVD) Among Middle-aged Individuals
Years Lived Free of and With Cardiovascular Disease (CVD) Among Middle-aged Individuals

Years lived free of and with CVD in middle-aged (index age, 40-59 years) men (A) and women (B). Participants with normal body mass index experienced greater years lived free of CVD compared with participants who were underweight, overweight, obese, or morbidly obese. Years lived with CVD was greater in participants in higher body mass index groups, accounting for a greater degree of life lived with morbidity in the context of similar or shorter overall survival. Compared with men and women with normal body mass index, men and women with morbid obesity had an accelerated onset of CVD by 7.5 and 7.1 years, respectively, and had reduced overall survival by 5.6 and 2.0 years.

Table 1.  
Baseline Characteristics and Body Mass Index Categories Among Men and Women According to Index Age Group
Baseline Characteristics and Body Mass Index Categories Among Men and Women According to Index Age Group
Table 2.  
Hazard Ratio and Cumulative Incidences for First Event Among Middle-aged Men and Women According to Body Mass Index Strataa
Hazard Ratio and Cumulative Incidences for First Event Among Middle-aged Men and Women According to Body Mass Index Strataa
Table 3.  
Adjusted Competing Hazard Ratiosa for First Event Among Middle-aged Men and Women According to Body Mass Index Stratab
Adjusted Competing Hazard Ratiosa for First Event Among Middle-aged Men and Women According to Body Mass Index Stratab
Supplement.

eMethods. Cardiovascular Disease Lifetime Risk Pooling Project supplemental methods.

eFigure 1. Lifetime risk of cardiovascular and noncardiovascular mortality among middle-aged men and women (index age, 40-59 years) based on body mass index strata and adjusted for competing risks.

eFigure 2. Lifetime risk of cardiovascular events and noncardiovascular mortality among older men and women (index age, 60-79 years) based on body mass index strata and adjusted for competing risks.

eFigure 3. Lifetime risk of cardiovascular events and noncardiovascular mortality among young men and women (index age, 20-39 years) based on body mass index strata and adjusted for competing risks.

eFigure 4. Years lived free from and with cardiovascular disease among young men and women (index age, 20-39 years) by body mass index strata.

eFigure 5. Years lived free from and with cardiovascular disease among older men and women (index age, 60-79 years) by body mass index strata.

eTable 1. Risk factors and unadjusted event rates for young men and women (index age, 20-39 years) by body mass index strata.

eTable 2. Risk factors and unadjusted event rates for middle-aged men and women (index age, 40-59 years) by body mass index strata.

eTable 3. Risk factors and unadjusted event rates for older men and women (index age, 60-79 years) by body mass index strata.

eTable 4. Cumulative incidences for CVD death or non-CVD death among middle-aged men and women (index age, 40-59 years) according to body mass index strata.

eTable 5. Cumulative incidences for first event (CVD event or non-CVD death) among young men and women (index age, 20-39 years) according to body mass index strata.

eTable 6. Cumulative incidences for first event (CVD event or non-CVD death) among older men and women (index age, 60-79 years) according to body mass index strata.

eTable 7. Adjusted competing hazard ratios for CVD death or non-CVD death among middle-aged men and women (index age, 40-59 years) according to body mass index strata.

eTable 8. Adjusted competing hazard ratios for first event (CVD event or non-CVD death) among young men and women (index age, 20-39 years) according to body mass index strata.

eTable 9. Adjusted competing hazard ratios for first event (CVD event or non-CVD death) among older men and women (index age, 60-79 years) according to body mass index strata.

eTable 10. Summary of years lived (means and standard errors) free from and with cardiovascular disease (CVD) by index age groups, sex, and body mass index strata.

1.
Benjamin  EJ, Blaha  MJ, Chiuve  SE,  et al; American Heart Association Statistics Committee and Stroke Statistics Subcommittee.  Heart Disease and Stroke Statistics—2017 update: a report from the American Heart Association.  Circulation. 2017;135(10):e146-e603.PubMedGoogle ScholarCrossref
2.
Ng  M, Fleming  T, Robinson  M,  et al.  Global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013: a systematic analysis for the Global Burden of Disease Study 2013.  Lancet. 2014;384(9945):766-781.PubMedGoogle ScholarCrossref
3.
Flegal  KM, Kit  BK, Orpana  H, Graubard  BI.  Association of all-cause mortality with overweight and obesity using standard body mass index categories: a systematic review and meta-analysis.  JAMA. 2013;309(1):71-82.PubMedGoogle ScholarCrossref
4.
Flegal  KM, Graubard  BI, Williamson  DF, Gail  MH.  Excess deaths associated with underweight, overweight, and obesity.  JAMA. 2005;293(15):1861-1867.PubMedGoogle ScholarCrossref
5.
Mozaffarian  D, Benjamin  EJ, Go  AS,  et al; Writing Group Members; American Heart Association Statistics Committee; Stroke Statistics Subcommittee.  Heart Disease and Stroke Statistics—2016 update: a report from the American Heart Association.  Circulation. 2016;133(4):e38-e360.PubMedGoogle ScholarCrossref
6.
Wang  Y, Beydoun  MA, Liang  L, Caballero  B, Kumanyika  SK.  Will all Americans become overweight or obese? estimating the progression and cost of the US obesity epidemic.  Obesity (Silver Spring). 2008;16(10):2323-2330.PubMedGoogle ScholarCrossref
7.
Ogden  CL, Carroll  MD, Fryar  CD, Flegal  KM.  Prevalence of obesity among adults and youth: United States, 2011-2014.  NCHS Data Brief. 2015;(219):1-8.PubMedGoogle Scholar
8.
Flegal  KM, Kruszon-Moran  D, Carroll  MD, Fryar  CD, Ogden  CL.  Trends in obesity among adults in the United States, 2005 to 2014.  JAMA. 2016;315(21):2284-2291.PubMedGoogle ScholarCrossref
9.
Ogden  CL, Carroll  MD, Lawman  HG,  et al.  Trends in obesity prevalence among children and adolescents in the United States, 1988-1994 through 2013-2014.  JAMA. 2016;315(21):2292-2299.PubMedGoogle ScholarCrossref
10.
Wilkins  JT, Karmali  KN, Huffman  MD,  et al.  Data resource profile: the Cardiovascular Disease Lifetime Risk Pooling Project.  Int J Epidemiol. 2015;44(5):1557-1564.PubMedGoogle ScholarCrossref
11.
The ARIC Investigators.  The Atherosclerosis Risk in Communities (ARIC) Study: design and objectives.  Am J Epidemiol. 1989;129(4):687-702.PubMedGoogle ScholarCrossref
12.
Friedman  GD, Cutter  GR, Donahue  RP,  et al.  CARDIA: study design, recruitment, and some characteristics of the examined subjects.  J Clin Epidemiol. 1988;41(11):1105-1116.PubMedGoogle ScholarCrossref
13.
Stamler  J, Rhomberg  P, Schoenberger  JA,  et al.  Multivariate analysis of the relationship of seven variables to blood pressure: findings of the Chicago Heart Association Detection Project in Industry, 1967-1972.  J Chronic Dis. 1975;28(10):527-548.PubMedGoogle ScholarCrossref
14.
Stamler  J, Dyer  AR, Shekelle  RB, Neaton  J, Stamler  R.  Relationship of baseline major risk factors to coronary and all-cause mortality, and to longevity: findings from long-term follow-up of Chicago cohorts.  Cardiology. 1993;82(2-3):191-222.PubMedGoogle ScholarCrossref
15.
Fried  LP, Borhani  NO, Enright  P,  et al.  The Cardiovascular Health Study: design and rationale.  Ann Epidemiol. 1991;1(3):263-276.PubMedGoogle ScholarCrossref
16.
Dawber  TR, Kannel  WB, Lyell  LP.  An approach to longitudinal studies in a community: the Framingham Study.  Ann N Y Acad Sci. 1963;107:539-556.PubMedGoogle ScholarCrossref
17.
Kannel  WB, Feinleib  M, McNamara  PM, Garrison  RJ, Castelli  WP.  An investigation of coronary heart disease in families: the Framingham Offspring Study.  Am J Epidemiol. 1979;110(3):281-290.PubMedGoogle ScholarCrossref
18.
Haan  MN, Selby  JV, Rice  DP,  et al.  Trends in cardiovascular disease incidence and survival in the elderly.  Ann Epidemiol. 1996;6(4):348-356.PubMedGoogle ScholarCrossref
19.
Bild  DE, Bluemke  DA, Burke  GL,  et al.  Multi-Ethnic Study of Atherosclerosis: objectives and design.  Am J Epidemiol. 2002;156(9):871-881.PubMedGoogle ScholarCrossref
20.
Cohen  BB, Barbano  HE, Cox  CS,  et al.  Plan and operation of the NHANES I Epidemiologic Followup Study: 1982-84.  Vital Health Stat 1. 1987;22(22):1-142.PubMedGoogle Scholar
21.
The Women’s Health Initiative Study Group.  Design of the Women’s Health Initiative clinical trial and observational study.  Control Clin Trials. 1998;19(1):61-109.PubMedGoogle ScholarCrossref
22.
Gawron  A, Hou  L, Ning  H, Berry  JD, Lloyd-Jones  DM.  Lifetime risk for cancer death by sex and smoking status: the Lifetime Risk Pooling Project.  Cancer Causes Control. 2012;23(10):1729-1737.PubMedGoogle ScholarCrossref
23.
Beiser  A, D’Agostino  RB  Sr, Seshadri  S, Sullivan  LM, Wolf  PA.  Computing estimates of incidence, including lifetime risk: Alzheimer’s disease in the Framingham Study: the Practical Incidence Estimators (PIE) macro.  Stat Med. 2000;19(11-12):1495-1522.PubMedGoogle ScholarCrossref
24.
Lunn  M, McNeil  D.  Applying Cox regression to competing risks.  Biometrics. 1995;51(2):524-532.PubMedGoogle ScholarCrossref
25.
Fine  JP, Gray  RJ.  A proportional hazards model for the subdistribution of a competing risk.  J Am Stat Assoc. 1999;94:496-509. doi:10.2307/2670170Google ScholarCrossref
26.
Karrison  TG.  Use of Irwin’s restricted mean as an index for comparing survival in different treatment groups: interpretation and power considerations.  Control Clin Trials. 1997;18(2):151-167.PubMedGoogle ScholarCrossref
27.
Wilkins  JT, Ning  H, Berry  J, Zhao  L, Dyer  AR, Lloyd-Jones  DM.  Lifetime risk and years lived free of total cardiovascular disease.  JAMA. 2012;308(17):1795-1801.PubMedGoogle ScholarCrossref
28.
Wilson  PW, D’Agostino  RB, Sullivan  L, Parise  H, Kannel  WB.  Overweight and obesity as determinants of cardiovascular risk: the Framingham experience.  Arch Intern Med. 2002;162(16):1867-1872.PubMedGoogle ScholarCrossref
29.
Kenchaiah  S, Evans  JC, Levy  D,  et al.  Obesity and the risk of heart failure.  N Engl J Med. 2002;347(5):305-313.PubMedGoogle ScholarCrossref
30.
Ndumele  CE, Matsushita  K, Lazo  M,  et al.  Obesity and subtypes of incident cardiovascular disease.  J Am Heart Assoc. 2016;5(8):e003921.PubMedGoogle ScholarCrossref
31.
Dhana  K, Berghout  MA, Peeters  A,  et al.  Obesity in older adults and life expectancy with and without cardiovascular disease.  Int J Obes (Lond). 2016;40(10):1535-1540.PubMedGoogle ScholarCrossref
32.
Reuser  M, Bonneux  L, Willekens  F.  The burden of mortality of obesity at middle and old age is small: a life table analysis of the US Health and Retirement Survey.  Eur J Epidemiol. 2008;23(9):601-607.PubMedGoogle ScholarCrossref
33.
Pardo Silva  MC, De Laet  C, Nusselder  WJ, Mamun  AA, Peeters  A.  Adult obesity and number of years lived with and without cardiovascular disease.  Obesity (Silver Spring). 2006;14(7):1264-1273.PubMedGoogle ScholarCrossref
34.
Nyholm  M, Gullberg  B, Merlo  J, Lundqvist-Persson  C, Råstam  L, Lindblad  U.  The validity of obesity based on self-reported weight and height: implications for population studies.  Obesity (Silver Spring). 2007;15(1):197-208.PubMedGoogle ScholarCrossref
35.
Lavie  CJ, Milani  RV, Ventura  HO.  Obesity and cardiovascular disease: risk factor, paradox, and impact of weight loss.  J Am Coll Cardiol. 2009;53(21):1925-1932.PubMedGoogle ScholarCrossref
36.
Locher  JL, Roth  DL, Ritchie  CS,  et al.  Body mass index, weight loss, and mortality in community-dwelling older adults.  J Gerontol A Biol Sci Med Sci. 2007;62(12):1389-1392.PubMedGoogle ScholarCrossref
37.
Tobias  DK, Hu  FB.  Does being overweight really reduce mortality?  Obesity (Silver Spring). 2013;21(9):1746-1749.PubMedGoogle ScholarCrossref
38.
Jee  SH, Sull  JW, Park  J,  et al.  Body-mass index and mortality in Korean men and women.  N Engl J Med. 2006;355(8):779-787.PubMedGoogle ScholarCrossref
39.
Berrington de Gonzalez  A, Hartge  P, Cerhan  JR,  et al.  Body-mass index and mortality among 1.46 million white adults.  N Engl J Med. 2010;363(23):2211-2219.PubMedGoogle ScholarCrossref
40.
Pischon  T, Boeing  H, Hoffmann  K,  et al.  General and abdominal adiposity and risk of death in Europe.  N Engl J Med. 2008;359(20):2105-2120.PubMedGoogle ScholarCrossref
41.
Whitlock  G, Lewington  S, Sherliker  P,  et al; Prospective Studies Collaboration.  Body-mass index and cause-specific mortality in 900 000 adults: collaborative analyses of 57 prospective studies.  Lancet. 2009;373(9669):1083-1096.PubMedGoogle ScholarCrossref
42.
Zheng  W, McLerran  DF, Rolland  B,  et al.  Association between body-mass index and risk of death in more than 1 million Asians.  N Engl J Med. 2011;364(8):719-729.PubMedGoogle ScholarCrossref
43.
Giuli  C, Papa  R, Bevilacqua  R,  et al.  Correlates of perceived health related quality of life in obese, overweight and normal weight older adults: an observational study.  BMC Public Health. 2014;14:35.PubMedGoogle ScholarCrossref
44.
Armour  BS, Courtney-Long  E, Campbell  VA, Wethington  HR.  Estimating disability prevalence among adults by body mass index: 2003-2009 National Health Interview Survey.  Prev Chronic Dis. 2012;9:E178.PubMedGoogle ScholarCrossref
45.
Daviglus  ML, Liu  K, Yan  LL,  et al.  Relation of body mass index in young adulthood and middle age to Medicare expenditures in older age.  JAMA. 2004;292(22):2743-2749.PubMedGoogle ScholarCrossref
46.
Flegal  KM, Carroll  MD, Ogden  CL, Johnson  CL.  Prevalence and trends in obesity among US adults, 1999-2000.  JAMA. 2002;288(14):1723-1727.PubMedGoogle ScholarCrossref
47.
US Centers for Disease Control and Prevention. Crude and age-adjusted death rates for all causes: 2014—quarter 3. http://www.cdc.gov/nchs/products/vsrr/mortality-dashboard.htm. Accessed June 1, 2016.
48.
Ford  ES, Ajani  UA, Croft  JB,  et al.  Explaining the decrease in US deaths from coronary disease, 1980-2000.  N Engl J Med. 2007;356(23):2388-2398.PubMedGoogle ScholarCrossref
49.
Ford  ES, Capewell  S.  Coronary heart disease mortality among young adults in the US from 1980 through 2002: concealed leveling of mortality rates.  J Am Coll Cardiol. 2007;50(22):2128-2132.PubMedGoogle ScholarCrossref
50.
Khan  SS, Shah  SJ, Liu  KJ,  et al.  Abstract 13246: the impact of body-mass index trajectories during early adulthood on cardiac mechanics in middle age: the CARDIA Study.  Circulation. 2014;130(suppl 2):A13246.Google Scholar
51.
Clarke  P, O’Malley  PM, Johnston  LD, Schulenberg  JE.  Social disparities in BMI trajectories across adulthood by gender, race/ethnicity and lifetime socio-economic position: 1986-2004.  Int J Epidemiol. 2009;38(2):499-509.PubMedGoogle ScholarCrossref
52.
Jensen  MD, Ryan  DH, Apovian  CM,  et al; American College of Cardiology/American Heart Association Task Force on Practice Guidelines; Obesity Society.  2013 AHA/ACC/TOS guideline for the management of overweight and obesity in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and the Obesity Society.  Circulation. 2014;129(25, suppl 2):S102-S138.PubMedGoogle ScholarCrossref
Original Investigation
April 2018

Association of Body Mass Index With Lifetime Risk of Cardiovascular Disease and Compression of Morbidity

Author Affiliations
  • 1Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois
  • 2Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois
  • 3Division of Cardiology, University of Texas Southwestern Medical Center, Dallas
  • 4Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas
JAMA Cardiol. 2018;3(4):280-287. doi:10.1001/jamacardio.2018.0022
Key Points

Question  What is the association of body mass index with cardiovascular disease (CVD) morbidity and mortality?

Findings  In this population-based study, overweight and obesity were associated with significantly increased risk for CVD. Obesity was associated with shorter longevity and a greater proportion of life lived with CVD; overweight was associated with similar longevity as normal weight but at the expense of a greater proportion of life lived with CVD.

Meaning  These results provide critical perspective on CVD associated with overweight and obesity and challenge both the obesity paradox as well as the view that overweight is associated with greater longevity.

Abstract

Importance  Prior studies have demonstrated lower all-cause mortality in individuals who are overweight compared with those with normal body mass index (BMI), but whether this may come at the cost of greater burden of cardiovascular disease (CVD) is unknown.

Objective  To calculate lifetime risk estimates of incident CVD and subtypes of CVD and to estimate years lived with and without CVD by weight status.

Design, Setting, and Participants  In this population-based study, we used pooled individual-level data from adults (baseline age, 20-39, 40-59, and 60-79 years) across 10 large US prospective cohorts, with 3.2 million person-years of follow-up from 1964 to 2015. All participants were free of clinical CVD at baseline with available BMI index and CVD outcomes data. Data were analyzed from October 2016 to July 2017.

Exposures  World Health Organization–standardized BMI categories.

Main Outcomes and Measures  Total CVD and CVD subtype, including fatal and nonfatal coronary heart disease, stroke, congestive heart failure, and other CVD deaths. Heights and weights were measured directly by investigators in each study, and BMI was calculated as weight in kilograms divided by height in meters squared. We performed (1) modified Kaplan-Meier analysis to estimate lifetime risks, (2) adjusted competing Cox models to estimate joint cumulative risks for CVD or noncardiovascular death, and (3) the Irwin restricted mean to estimate years lived free of and with CVD.

Results  Of the 190 672 in-person examinations included in this study, the mean (SD) age was 46.0 (15.0) years for men and 58.7 (12.9) years for women, and 140 835 patients (73.9%) were female. Compared with individuals with a normal BMI (defined as a BMI of 18.5 to 24.9), lifetime risks for incident CVD were higher in middle-aged adults in the overweight and obese groups. Compared with normal weight, among middle-aged men and women, competing hazard ratios for incident CVD were 1.21 (95% CI, 1.14-1.28) and 1.32 (95% CI, 1.24-1.40), respectively, for overweight (BMI, 25.0-29.9), 1.67 (95% CI, 1.55-1.79) and 1.85 (95% CI, 1.72-1.99) for obesity (BMI, 30.0-39.9), and 3.14 (95% CI, 2.48-3.97) and 2.53 (95% CI, 2.20-2.91) for morbid obesity (BMI, ≥40.0). Higher BMI had the strongest association with incident heart failure among CVD subtypes. Average years lived with CVD were longer for middle-aged adults in the overweight and obese groups compared with adults in the normal BMI group. Similar patterns were observed in younger and older adults.

Conclusions and Relevance  In this study, obesity was associated with shorter longevity and significantly increased risk of cardiovascular morbidity and mortality compared with normal BMI. Despite similar longevity compared with normal BMI, overweight was associated with significantly increased risk of developing CVD at an earlier age, resulting in a greater proportion of life lived with CVD morbidity.

Introduction

Overweight and obesity are highly prevalent in the United States, have increased dramatically over the past 3 decades, and affect approximately 2.1 billion adults worldwide.1,2 In recent years, controversy about the health implications of overweight status (ie, body mass index [BMI, calculated as weight in kilograms divided by height in meters squared] of 25.0 to 29.9) has grown, given findings of similar or lower all-cause mortality rates in overweight compared with normal-weight groups.3,4 However, current studies have not taken into account the age at onset and duration of cardiovascular disease (CVD), limiting the ability to account for proportion of life lived with CVD morbidity in individuals who are overweight and obese compared with normal weight. This is especially important because disease burden associated with development of CVD results in less healthful years of life, poorer quality of life, and increased health care expenditures.5,6

Estimates of lifetime risk of CVD offer a more comprehensive assessment of the overall burden of CVD morbidity in the general population, allow adjustment for competing risks (eg, noncardiovascular mortality), and can help guide public health policy regarding weight guidelines by offering projections of the overall burden of CVD by weight status in the population. Such estimates are especially important given competing risks of concomitant non-CVD morbidity seen with excess weight. Upward shifts in the prevalence of obesity in the past several decades, including continued increases among adolescents, raise concern for future population-level burden of cardiovascular morbidity and mortality associated with excess weight.7-9

Our objectives were to calculate lifetime risk estimates of incident total CVD and subtypes of CVD and to estimate years lived with and without CVD by weight status in adults (aged 20 to 89 years). We hypothesized that compared with normal BMI, overweight would be associated with greater lifetime CVD risk even after consideration of competing risks from non-CVD death, fewer years lived free of CVD, and greater life-years lived with CVD.

Methods

The Cardiovascular Disease Lifetime Risk Pooling Project10 collected and pooled individual-level data from numerous longitudinal population-based cohort studies conducted in the United States over the past 7 decades. This pooling approach offers the opportunity to calculate estimates of lifetime risk of CVD events and estimates of years lived free of CVD according to age and BMI categories, which would not be feasible within 1 data set alone. It includes participants free of clinical CVD across the life course from young adulthood to older adulthood, with nearly 100% complete follow-up for vital status. We included data from participants who were free of clinical CVD at baseline from the following 10 prospective cohort studies in the Cardiovascular Disease Lifetime Risk Pooling Project10: the Atherosclerosis Risk in Communities Study,11 the Coronary Artery Risk Development in Young Adults Study,12 the Chicago Heart Association Detection Project in Industry Study,13,14 the Cardiovascular Health Study,15 the Framingham Heart Study,16 the Framingham Offspring Study,17 the Kaiser Permanente Study of the Oldest Old,18 the Multi-Ethnic Study of Atherosclerosis,19 the National Health and Nutrition Examination Survey I Epidemiologic Follow-up Study,20 and the Women’s Health Initiative.21 All included cohorts represented community-based or population-based samples with at least 1 examination that included direct measurement of weight and height, at least 10 years of follow-up, and surveillance and adjudication for all subtypes of cardiovascular events of interest (ie, fatal and nonfatal myocardial infarction, fatal and nonfatal stroke, congestive heart failure [HF], and cardiovascular death) and noncardiovascular death (eMethods in the Supplement). This included 190 672 person-examinations across the life course, with 3.2 million person-years of follow-up until 2015. Individual participants were stratified by index age groups (young, aged 20 to 39 years; middle-aged, aged 40 to 59 years; and older, aged 60 to 79 years), sex, and BMI strata. All data were deidentified, and all study protocols and procedures were approved by the institutional review board at Northwestern University with a waiver for informed consent.

The protocols used to obtain data on demographic characteristics, physical examination results, laboratory results, and follow-up procedures for ascertainment of vital status and events for all cohorts have been previously published (eMethods in the Supplement).10 Height, weight, blood pressure level, fasting glucose level, and total cholesterol level were measured directly in all participants; smoking status was self-reported. Incident cardiovascular events were ascertained with the use of strategies selected by each cohort’s investigator group. Nonfatal CVD events of interest included myocardial infarction, stroke, and HF, and fatal events were stratified as death caused by CVD, coronary heart disease (CHD), or non-CVD events.

All statistical analyses were performed with SAS version 9.2 (SAS Institute) and R version 3.1.2 (The R Foundation). For calculation of lifetime risk, we used a modified Kaplan-Meier analysis, which accounts for competing risks for non-CVD death, as previously described.22,23 In brief, the modified Kaplan-Meier analysis accounts for fatal events from non-CVD causes as a separate end point rather than a censoring event. Rates of CVD death, CHD, HF, and stroke were calculated for each index age group to age 95 years, or the oldest age with robust person-time, to estimate lifetime risk of total CVD.

We calculated cumulative risk for CVD events and non-CVD death by BMI strata in age-stratified and sex-stratified analyses. We determined the proportion of incident first events (CVD event or non-CVD death) that occurred during the follow-up time. In these analyses, the occurrence of one type of event precluded consideration of another CVD event or non-CVD death event in that participant. We used the data augmentation method as described by Lunn and McNeil24 to fit Cox proportional hazard models to estimate hazard ratios for all CVD events combined compared with non-CVD death as the first event within BMI strata. In separate analyses, we used the method described by Fine and Gray25 to estimate the competing hazards for each CVD event (ie, CHD, HF, stroke, and other CVD death) and non-CVD death by BMI strata and adjusted for age, race/ethnicity, and smoking status. In addition, we performed sensitivity analyses for estimating hazards in nonsmokers. The mean survival time or years lived free of CVD, with CVD, and overall were estimated using the Irwin restricted mean to assess differences in compression of morbidity by BMI strata.26

Results

A total of 190 672 person-examinations were included in the pooled cohort, of whom 23 331 (12.2%) were African American. As expected, older adults had a higher prevalence of diabetes and hypertension treatment and higher mean total cholesterol levels, whereas younger adults had a higher rate of smoking (Table 1). The proportion of adults in the underweight and morbidly obese groups was relatively small, ranging from 0.3% to 6.6%. Approximately two-thirds of adults were in the normal or overweight BMI categories. Baseline characteristics by BMI strata for young, middle-aged, and older adults are in eTables 1, 2, and 3, respectively, in the Supplement, with a higher prevalence of diabetes in the overweight and obese categories in all age groups. Only 233 participants (0.1%) died within the first 6 months of follow-up.

Lifetime Risks for Cardiovascular Events and Noncardiovascular Death by BMI Strata

During 856 523 person-years of follow-up in middle-aged adults (index age, 40-59 years), there were 7136 incident fatal or nonfatal myocardial infarctions, 3733 incident fatal or nonfatal strokes, 4614 diagnoses of incident congestive HF, and a total of 13 457 incident CVD events. Among middle-aged men, unadjusted rates of incident CVD events per thousand person-years were 13.72, 15.53, 20.21, and 30.15 in normal BMI, overweight, obese, and morbidly obese categories, respectively. In general, unadjusted rates of CVD were higher in men and women who are overweight and obese in all 3 age groups (eTables 1, 2, and 3 in the Supplement).

Among middle-aged men and women, adults who are overweight and obese had a higher cumulative lifetime risk of incident CVD events and CVD death compared with adults with normal BMI (Figure 1; eFigure 1 in the Supplement). The findings were similar in older adults (eFigure 2 in the Supplement). In young men and women, the findings were similar, with increased lifetime risk of incident CVD events in adults in the obese and morbidly obese groups but not in adults in the overweight group (eFigure 3 in the Supplement). There were marked differences across age and BMI strata in the patterns of lifetime risk of non-CVD death. Overall, 10 136 non-CVD deaths (40.8%) were related to cancer (eFigures 1, 2, and 3 in the Supplement).

Competing Risks of CVD Morbidity and Non-CVD Mortality by BMI Strata

The proportions of middle-aged adults who experienced incident CVD or non-CVD death stratified by sex and BMI groups are shown in Table 2. Incident CVD events occurred in more middle-aged men and women in overweight (37% and 28%, respectively), obese (47% and 39%), and morbidly obese (65% and 48%) strata compared with adults in the normal BMI group (32% and 22%). Adjusted competing hazard ratios (by the Lunn and McNeil method24) for experiencing a CVD event compared with non-CVD death were greater in higher BMI categories and were greatest in the morbidly obese category in middle-aged men and women, predominantly because of a greater proportion of CHD and HF events. In addition, greater all-cause mortality in higher BMI categories occurred at the expense of a greater proportion of deaths from cardiovascular causes in middle-aged men and women who are overweight and obese (eTable 4 in the Supplement). Similar patterns were seen in younger and older adults (eTables 5 and 6 in the Supplement).

Adjusted competing hazard ratios (by the Fine and Gray method25) for incident events in middle-aged men and women by BMI strata are shown in Table 3. Middle-aged men and women who are overweight, obese, and morbidly obese had significantly higher hazard ratios for incident CVD events compared with normal BMI, ranging from 1.21 to 3.14 across BMI categories. Among CVD subtypes, higher BMI was associated with greatest hazard ratios for incident HF. The adjusted competing hazard ratios of incident CVD events per unit of BMI in middle-aged men and women were 1.05 (95% CI, 1.05-1.06) and 1.05 (95% CI, 1.04-1.05), respectively. In addition, when examining only fatal events, risk of CVD death was significantly higher in excess BMI categories compared with normal BMI (eTable 7 in the Supplement). Similar increased hazard ratios of incident CVD events are seen in young and older men and women in excess weight BMI categories compared with normal BMI (eTables 8 and 9 in the Supplement). Sensitivity analysis in nonsmokers demonstrated similar patterns, with increased risk of CVD in excess weight BMI categories in all age groups (data not shown).

Years Lived Free of and With CVD

In middle-aged men, overall survival time was similar in the normal BMI (29.1 years) and overweight (29.3 years) groups and was significantly shorter in the obese (27.2 years) and morbidly obese (23.4 years) groups (eTable 10 in the Supplement). In middle-aged women, overall survival was longest in the normal BMI category (33.2 years) compared with women in higher BMI categories (overweight, 31.8 years; obese, 29.8 years; and morbidly obese, 27.2). Cardiovascular disease–free years were similar in middle-aged men in the normal BMI and overweight groups and were longer than men who were obese (Figure 2). Years lived free of CVD were greater in middle-aged women with normal BMI compared with women who were overweight or obese. Average years lived with CVD in middle-aged men and women were shortest in the normal BMI group compared with adults in higher BMI groups, resulting in relative compression of morbidity. Normal BMI significantly delayed the incidence of CVD in middle-aged men and women by an average of 7.5 and 7.1 years, respectively, compared with men and women with morbid obesity. In addition, on average, men and women with normal BMI lived 5.6 and 2.0 years, respectively, longer compared with men and women with morbid obesity, resulting in a significant relative and absolute compression of morbidity. Overall similar patterns were seen in younger and older men and women (eTable 4 and eFigures 4 and 5 in the Supplement).

Discussion

In this large study of US adults free of clinical CVD at baseline, lifetime risk for incident CVD was high for all adults and was greater in adults who were overweight and obese. Adults who were obese had an earlier onset of incident CVD, a greater proportion of life lived with CVD morbidity (unhealthy life years), and shorter overall survival compared with adults with normal BMI. In addition, the proportion of adults with incident CVD events (compared with non-CVD death) was significantly higher in adults who were overweight or obese compared with adults in the normal BMI group. Overweight and obesity were associated with increased hazards of incident CVD event after adjustment for competing risks of non-CVD death across all index age ranges. The results of this study build on prior research from the Cardiovascular Disease Lifetime Risk Pooling Project10 highlighting marked differences in lifetime risks of CVD and further highlight the importance of consideration of BMI as a risk factor for diminished healthy longevity and greater overall CVD morbidity and mortality.22,27

Overweight status and obesity were associated with higher risk of incident CVD overall and subtypes of CVD (ie, CHD and HF), which is a finding of considerable public health importance. Our findings are consistent with prior work from the Framingham Heart Study28,29 and the Atherosclerosis Risk in Communities study,30 which demonstrated increased risk of CVD in participants who were overweight and obese. Importantly, we noted the strongest association between BMI categories and HF compared with other subtypes of CVD, with a 5-fold increase in incident HF in middle-aged men with morbid obesity, which has particularly important implications for focusing on weight management strategies for HF prevention. In addition, our findings suggest that earlier occurrence of CVD in those with obesity is most strongly associated with a greater proportion of life lived with CVD and shorter overall survival in adults aged 20 to 59 years at baseline. However, the association of obesity with mortality may change at older ages, which may explain why earlier studies comprising participants from the Rotterdam Study31 and the US Health and Retirement Survey Study32 showed no difference in total life expectancy in older men and women with obesity. However, studies from the Framingham Heart Study reported greater differences in years lived free of CVD and total life expectancy in men and women with obesity.33 The difference between our findings and findings from prior analyses include the ability to stratify by age across the life course (young, middle-age, and older adulthood) and by severity of obesity (obese and morbidly obese) because of the inclusion of 10 large US cohorts with long-term follow-up.

While health hazards of obesity have long been recognized, recent studies3,4,34-36 have spurred controversy about the specific relationship between overweight status and mortality. In a 2013 meta-analysis,3 the summary hazard ratio (0.94; 95% CI, 0.91-0.96) for total mortality was significantly lower for overweight relative to normal BMI using data from 97 studies and 2.88 million adults. However, several large cohorts and studies37-42 were excluded from this meta-analysis, among which a separate analysis demonstrated the lowest mortality in adults with a BMI of 22.5 to 25.0. Further, overweight status was associated with lower number of absolute deaths (−86 094; 95% CI, −151 223 to −10 966) compared with normal BMI in an analysis from the National Health and Nutrition Examination Survey.4 Among these prior analyses, measurement bias may be present owing to inclusion of self-reported height and weight data. Further, inclusion of participants with comorbidities at baseline, specifically prevalent CVD, may contribute to selection and survival bias because of protopathic bias (reverse causation) related to unintentional weight loss.34-36 Finally, follow-up times varied significantly in prior studies. In our study, we were able to leverage long-term follow-up in a large group of adults free of CVD at baseline to estimate risk of incident CVD and associated CVD morbidity (unhealthy years lived with CVD). In addition, we performed stratified analyses of competing event risk adjustment accounting for differing risk for non-CVD death by age, sex, and BMI strata.

Assessment solely of all-cause mortality as an outcome measure indicating the presence of an overweight or obesity paradox does not incorporate morbidity and overall disease burden associated with excess weight, which has significant relevance for overall health, fitness, and health-related disability. While we do observe evidence of the well-described overweight and obesity paradox, in which heavier individuals appear to live longer on average after diagnosis of CVD compared with individuals with normal BMI, our data when following up individuals prior to the onset of CVD indicate that this occurs because of a trend toward earlier onset of disease in individuals who are overweight and obese. This false reassurance is akin to the phenomenon of lead-time bias observed in other situations, such as with cancer screening.35 This is especially important because overweight status has been associated with poorer quality of life, functional impairment, and greater work-related disability.43,44 In addition, prior studies45 have demonstrated that this excess weight–associated morbidity and disability translates into greater health care costs with higher average annual and cumulative Medicare charges (both CVD related and total). Importantly, our study specifically included nonfatal cardiovascular events to incorporate assessment of cardiovascular morbidity and highlight the broad effect of excess weight.

Population-based prevalence of obesity among adults in the United States has increased dramatically from the 1980s and 1990s and has subsequently plateaued in the last decade, with current estimates of 35% among men and 41% among women.7,46 Trends in overweight, obesity, and extreme obesity through childhood and adolescence have also increased at alarming rates over the past 5 decades.9 Preliminary data from the US Centers for Disease Control and Prevention demonstrate increases in age-adjusted death rates for the first 9 months of 2015, with relative increases in mortality rates for obesity-related causes of death, including heart disease (1%), stroke (4%), and diabetes (1%).47 In addition, data published in 2007 also suggest a slowing of reductions in coronary death rates and a growing number of hospitalizations for acute and chronic manifestations of CVD, such as HF.48,49 These trends are concerning for very likely future increases in the population-level burden of CVD among adults, including a trend for CVD events to occur at younger ages. The economic implications of direct and indirect medical costs of the overweight and obesity epidemic are enormous, and total health care costs attributable to overweight and obesity are estimated to exceed $800 billion by 2030 if current trends persist.5,6

Strengths and Limitations

Strengths of our study include the large sample size of adults free of CVD at baseline, direct measurement of height and weight with standardized BMI categories, and extended follow-up with adjudicated CVD events by type and non-CVD death across the life course, which makes the findings robust and generalizable. Additionally, our cohorts included a representative sample of women and African American patients without significant cohort effects on our findings.

Limitations of our study include the use of baseline BMI at index ages without accounting for change in BMI across follow-up. However, recent analyses using latent class model trajectories in population-based cohorts highlight that there is significant tracking of BMI from young adulthood to middle-age with weight gain in all strata regardless of baseline BMI.50,51 In addition, use of BMI does not account for fat distribution or degree of visceral adiposity, but measures of central adiposity were not universally available across our component studies40,52; however, BMI is the most clinically relevant measure and allows broader generalizability of findings. Additional important outcomes of obesity-related morbidity, such as atrial fibrillation, sleep-disordered breathing, and chronic liver disease, were not ascertained routinely in our cohort studies, and we likely underestimated the overall comorbidity burden of excess weight.

Conclusions

In summary, we present an analysis of data from 190 672 in-person examinations derived from 10 population-based cohorts during a period of more than 50 years. We found that overweight status, in addition to obesity, is associated with significantly increased long-term risk for CVD morbidity in the context of similar or shorter total longevity and a greater proportion of life lived with morbidity compared with normal BMI. These findings were consistent across all index age groups ranging from young to older adulthood (20 to 89 years). Our results provide critical perspective on the cardiovascular disease burden associated with overweight, highlight unhealthy years lived with increased cardiovascular morbidity, and challenge the prevalent view that overweight is associated with greater longevity compared with normal BMI. Overweight does not appear to be associated with significantly greater longevity, and there is greater burden of CVD during that lifespan. Taking a life course perspective, we observe that the obesity paradox (ie, greater longevity after diagnosis of CVD for those who are overweight and obese) appears largely to be caused by earlier diagnosis of CVD. Study of inception cohorts of people at the time of CVD diagnosis would not detect this finding, leading to unclear messaging about the true risks of being overweight.

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Article Information

Accepted for Publication: January 5, 2018.

Corresponding Author: Sadiya S. Khan, MD, MS, Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, 680 N Lake Shore Dr, 14-002, Chicago, IL 60611 (s-khan-1@northwestern.edu).

Published Online: February 28, 2018. doi:10.1001/jamacardio.2018.0022

Author Contributions: Drs Khan and Lloyd-Jones had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Khan, Wilkins, Carnethon, Sweis, Lloyd-Jones.

Acquisition, analysis, or interpretation of data: Khan, Ning, Wilkins, Allen, Berry, Sweis, Lloyd-Jones.

Drafting of the manuscript: Khan, Sweis, Lloyd-Jones.

Critical revision of the manuscript for important intellectual content: Khan, Ning, Wilkins, Allen, Carnethon, Berry, Lloyd-Jones.

Statistical analysis: Ning, Sweis.

Obtained funding: Khan, Lloyd-Jones.

Administrative, technical, or material support: Wilkins, Lloyd-Jones.

Study supervision: Wilkins, Carnethon, Lloyd-Jones.

Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.

Funding/Support: This study was supported by grants R21 HL085375 (Dr Lloyd-Jones) and F32 HL129695 (Dr Khan) from the National Heart, Lung, and Blood Institute.

Role of the Funder/Sponsor: The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Additional Contributions: We thank the investigators of all the cohort studies included in this analysis for their hard work and dedication in collecting the underlying data. We also thank the study participants, whose time and commitment have transformed our understanding of health and disease.

References
1.
Benjamin  EJ, Blaha  MJ, Chiuve  SE,  et al; American Heart Association Statistics Committee and Stroke Statistics Subcommittee.  Heart Disease and Stroke Statistics—2017 update: a report from the American Heart Association.  Circulation. 2017;135(10):e146-e603.PubMedGoogle ScholarCrossref
2.
Ng  M, Fleming  T, Robinson  M,  et al.  Global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013: a systematic analysis for the Global Burden of Disease Study 2013.  Lancet. 2014;384(9945):766-781.PubMedGoogle ScholarCrossref
3.
Flegal  KM, Kit  BK, Orpana  H, Graubard  BI.  Association of all-cause mortality with overweight and obesity using standard body mass index categories: a systematic review and meta-analysis.  JAMA. 2013;309(1):71-82.PubMedGoogle ScholarCrossref
4.
Flegal  KM, Graubard  BI, Williamson  DF, Gail  MH.  Excess deaths associated with underweight, overweight, and obesity.  JAMA. 2005;293(15):1861-1867.PubMedGoogle ScholarCrossref
5.
Mozaffarian  D, Benjamin  EJ, Go  AS,  et al; Writing Group Members; American Heart Association Statistics Committee; Stroke Statistics Subcommittee.  Heart Disease and Stroke Statistics—2016 update: a report from the American Heart Association.  Circulation. 2016;133(4):e38-e360.PubMedGoogle ScholarCrossref
6.
Wang  Y, Beydoun  MA, Liang  L, Caballero  B, Kumanyika  SK.  Will all Americans become overweight or obese? estimating the progression and cost of the US obesity epidemic.  Obesity (Silver Spring). 2008;16(10):2323-2330.PubMedGoogle ScholarCrossref
7.
Ogden  CL, Carroll  MD, Fryar  CD, Flegal  KM.  Prevalence of obesity among adults and youth: United States, 2011-2014.  NCHS Data Brief. 2015;(219):1-8.PubMedGoogle Scholar
8.
Flegal  KM, Kruszon-Moran  D, Carroll  MD, Fryar  CD, Ogden  CL.  Trends in obesity among adults in the United States, 2005 to 2014.  JAMA. 2016;315(21):2284-2291.PubMedGoogle ScholarCrossref
9.
Ogden  CL, Carroll  MD, Lawman  HG,  et al.  Trends in obesity prevalence among children and adolescents in the United States, 1988-1994 through 2013-2014.  JAMA. 2016;315(21):2292-2299.PubMedGoogle ScholarCrossref
10.
Wilkins  JT, Karmali  KN, Huffman  MD,  et al.  Data resource profile: the Cardiovascular Disease Lifetime Risk Pooling Project.  Int J Epidemiol. 2015;44(5):1557-1564.PubMedGoogle ScholarCrossref
11.
The ARIC Investigators.  The Atherosclerosis Risk in Communities (ARIC) Study: design and objectives.  Am J Epidemiol. 1989;129(4):687-702.PubMedGoogle ScholarCrossref
12.
Friedman  GD, Cutter  GR, Donahue  RP,  et al.  CARDIA: study design, recruitment, and some characteristics of the examined subjects.  J Clin Epidemiol. 1988;41(11):1105-1116.PubMedGoogle ScholarCrossref
13.
Stamler  J, Rhomberg  P, Schoenberger  JA,  et al.  Multivariate analysis of the relationship of seven variables to blood pressure: findings of the Chicago Heart Association Detection Project in Industry, 1967-1972.  J Chronic Dis. 1975;28(10):527-548.PubMedGoogle ScholarCrossref
14.
Stamler  J, Dyer  AR, Shekelle  RB, Neaton  J, Stamler  R.  Relationship of baseline major risk factors to coronary and all-cause mortality, and to longevity: findings from long-term follow-up of Chicago cohorts.  Cardiology. 1993;82(2-3):191-222.PubMedGoogle ScholarCrossref
15.
Fried  LP, Borhani  NO, Enright  P,  et al.  The Cardiovascular Health Study: design and rationale.  Ann Epidemiol. 1991;1(3):263-276.PubMedGoogle ScholarCrossref
16.
Dawber  TR, Kannel  WB, Lyell  LP.  An approach to longitudinal studies in a community: the Framingham Study.  Ann N Y Acad Sci. 1963;107:539-556.PubMedGoogle ScholarCrossref
17.
Kannel  WB, Feinleib  M, McNamara  PM, Garrison  RJ, Castelli  WP.  An investigation of coronary heart disease in families: the Framingham Offspring Study.  Am J Epidemiol. 1979;110(3):281-290.PubMedGoogle ScholarCrossref
18.
Haan  MN, Selby  JV, Rice  DP,  et al.  Trends in cardiovascular disease incidence and survival in the elderly.  Ann Epidemiol. 1996;6(4):348-356.PubMedGoogle ScholarCrossref
19.
Bild  DE, Bluemke  DA, Burke  GL,  et al.  Multi-Ethnic Study of Atherosclerosis: objectives and design.  Am J Epidemiol. 2002;156(9):871-881.PubMedGoogle ScholarCrossref
20.
Cohen  BB, Barbano  HE, Cox  CS,  et al.  Plan and operation of the NHANES I Epidemiologic Followup Study: 1982-84.  Vital Health Stat 1. 1987;22(22):1-142.PubMedGoogle Scholar
21.
The Women’s Health Initiative Study Group.  Design of the Women’s Health Initiative clinical trial and observational study.  Control Clin Trials. 1998;19(1):61-109.PubMedGoogle ScholarCrossref
22.
Gawron  A, Hou  L, Ning  H, Berry  JD, Lloyd-Jones  DM.  Lifetime risk for cancer death by sex and smoking status: the Lifetime Risk Pooling Project.  Cancer Causes Control. 2012;23(10):1729-1737.PubMedGoogle ScholarCrossref
23.
Beiser  A, D’Agostino  RB  Sr, Seshadri  S, Sullivan  LM, Wolf  PA.  Computing estimates of incidence, including lifetime risk: Alzheimer’s disease in the Framingham Study: the Practical Incidence Estimators (PIE) macro.  Stat Med. 2000;19(11-12):1495-1522.PubMedGoogle ScholarCrossref
24.
Lunn  M, McNeil  D.  Applying Cox regression to competing risks.  Biometrics. 1995;51(2):524-532.PubMedGoogle ScholarCrossref
25.
Fine  JP, Gray  RJ.  A proportional hazards model for the subdistribution of a competing risk.  J Am Stat Assoc. 1999;94:496-509. doi:10.2307/2670170Google ScholarCrossref
26.
Karrison  TG.  Use of Irwin’s restricted mean as an index for comparing survival in different treatment groups: interpretation and power considerations.  Control Clin Trials. 1997;18(2):151-167.PubMedGoogle ScholarCrossref
27.
Wilkins  JT, Ning  H, Berry  J, Zhao  L, Dyer  AR, Lloyd-Jones  DM.  Lifetime risk and years lived free of total cardiovascular disease.  JAMA. 2012;308(17):1795-1801.PubMedGoogle ScholarCrossref
28.
Wilson  PW, D’Agostino  RB, Sullivan  L, Parise  H, Kannel  WB.  Overweight and obesity as determinants of cardiovascular risk: the Framingham experience.  Arch Intern Med. 2002;162(16):1867-1872.PubMedGoogle ScholarCrossref
29.
Kenchaiah  S, Evans  JC, Levy  D,  et al.  Obesity and the risk of heart failure.  N Engl J Med. 2002;347(5):305-313.PubMedGoogle ScholarCrossref
30.
Ndumele  CE, Matsushita  K, Lazo  M,  et al.  Obesity and subtypes of incident cardiovascular disease.  J Am Heart Assoc. 2016;5(8):e003921.PubMedGoogle ScholarCrossref
31.
Dhana  K, Berghout  MA, Peeters  A,  et al.  Obesity in older adults and life expectancy with and without cardiovascular disease.  Int J Obes (Lond). 2016;40(10):1535-1540.PubMedGoogle ScholarCrossref
32.
Reuser  M, Bonneux  L, Willekens  F.  The burden of mortality of obesity at middle and old age is small: a life table analysis of the US Health and Retirement Survey.  Eur J Epidemiol. 2008;23(9):601-607.PubMedGoogle ScholarCrossref
33.
Pardo Silva  MC, De Laet  C, Nusselder  WJ, Mamun  AA, Peeters  A.  Adult obesity and number of years lived with and without cardiovascular disease.  Obesity (Silver Spring). 2006;14(7):1264-1273.PubMedGoogle ScholarCrossref
34.
Nyholm  M, Gullberg  B, Merlo  J, Lundqvist-Persson  C, Råstam  L, Lindblad  U.  The validity of obesity based on self-reported weight and height: implications for population studies.  Obesity (Silver Spring). 2007;15(1):197-208.PubMedGoogle ScholarCrossref
35.
Lavie  CJ, Milani  RV, Ventura  HO.  Obesity and cardiovascular disease: risk factor, paradox, and impact of weight loss.  J Am Coll Cardiol. 2009;53(21):1925-1932.PubMedGoogle ScholarCrossref
36.
Locher  JL, Roth  DL, Ritchie  CS,  et al.  Body mass index, weight loss, and mortality in community-dwelling older adults.  J Gerontol A Biol Sci Med Sci. 2007;62(12):1389-1392.PubMedGoogle ScholarCrossref
37.
Tobias  DK, Hu  FB.  Does being overweight really reduce mortality?  Obesity (Silver Spring). 2013;21(9):1746-1749.PubMedGoogle ScholarCrossref
38.
Jee  SH, Sull  JW, Park  J,  et al.  Body-mass index and mortality in Korean men and women.  N Engl J Med. 2006;355(8):779-787.PubMedGoogle ScholarCrossref
39.
Berrington de Gonzalez  A, Hartge  P, Cerhan  JR,  et al.  Body-mass index and mortality among 1.46 million white adults.  N Engl J Med. 2010;363(23):2211-2219.PubMedGoogle ScholarCrossref
40.
Pischon  T, Boeing  H, Hoffmann  K,  et al.  General and abdominal adiposity and risk of death in Europe.  N Engl J Med. 2008;359(20):2105-2120.PubMedGoogle ScholarCrossref
41.
Whitlock  G, Lewington  S, Sherliker  P,  et al; Prospective Studies Collaboration.  Body-mass index and cause-specific mortality in 900 000 adults: collaborative analyses of 57 prospective studies.  Lancet. 2009;373(9669):1083-1096.PubMedGoogle ScholarCrossref
42.
Zheng  W, McLerran  DF, Rolland  B,  et al.  Association between body-mass index and risk of death in more than 1 million Asians.  N Engl J Med. 2011;364(8):719-729.PubMedGoogle ScholarCrossref
43.
Giuli  C, Papa  R, Bevilacqua  R,  et al.  Correlates of perceived health related quality of life in obese, overweight and normal weight older adults: an observational study.  BMC Public Health. 2014;14:35.PubMedGoogle ScholarCrossref
44.
Armour  BS, Courtney-Long  E, Campbell  VA, Wethington  HR.  Estimating disability prevalence among adults by body mass index: 2003-2009 National Health Interview Survey.  Prev Chronic Dis. 2012;9:E178.PubMedGoogle ScholarCrossref
45.
Daviglus  ML, Liu  K, Yan  LL,  et al.  Relation of body mass index in young adulthood and middle age to Medicare expenditures in older age.  JAMA. 2004;292(22):2743-2749.PubMedGoogle ScholarCrossref
46.
Flegal  KM, Carroll  MD, Ogden  CL, Johnson  CL.  Prevalence and trends in obesity among US adults, 1999-2000.  JAMA. 2002;288(14):1723-1727.PubMedGoogle ScholarCrossref
47.
US Centers for Disease Control and Prevention. Crude and age-adjusted death rates for all causes: 2014—quarter 3. http://www.cdc.gov/nchs/products/vsrr/mortality-dashboard.htm. Accessed June 1, 2016.
48.
Ford  ES, Ajani  UA, Croft  JB,  et al.  Explaining the decrease in US deaths from coronary disease, 1980-2000.  N Engl J Med. 2007;356(23):2388-2398.PubMedGoogle ScholarCrossref
49.
Ford  ES, Capewell  S.  Coronary heart disease mortality among young adults in the US from 1980 through 2002: concealed leveling of mortality rates.  J Am Coll Cardiol. 2007;50(22):2128-2132.PubMedGoogle ScholarCrossref
50.
Khan  SS, Shah  SJ, Liu  KJ,  et al.  Abstract 13246: the impact of body-mass index trajectories during early adulthood on cardiac mechanics in middle age: the CARDIA Study.  Circulation. 2014;130(suppl 2):A13246.Google Scholar
51.
Clarke  P, O’Malley  PM, Johnston  LD, Schulenberg  JE.  Social disparities in BMI trajectories across adulthood by gender, race/ethnicity and lifetime socio-economic position: 1986-2004.  Int J Epidemiol. 2009;38(2):499-509.PubMedGoogle ScholarCrossref
52.
Jensen  MD, Ryan  DH, Apovian  CM,  et al; American College of Cardiology/American Heart Association Task Force on Practice Guidelines; Obesity Society.  2013 AHA/ACC/TOS guideline for the management of overweight and obesity in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and the Obesity Society.  Circulation. 2014;129(25, suppl 2):S102-S138.PubMedGoogle ScholarCrossref
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