[Skip to Content]
Access to paid content on this site is currently suspended due to excessive activity being detected from your IP address 18.204.227.250. Please contact the publisher to request reinstatement.
[Skip to Content Landing]
Table 1.  
Baseline Characteristics of the Study Population (N = 156 624) According to Different Combinations of Body Mass Index and WCa
Baseline Characteristics of the Study Population (N = 156 624) According to Different Combinations of Body Mass Index and WCa
Table 2.  
Association of Different Combinations of Body Mass Index and WC Status With All-Cause and Cause-Specific Mortality Among 156 624 Postmenopausal Womena
Association of Different Combinations of Body Mass Index and WC Status With All-Cause and Cause-Specific Mortality Among 156 624 Postmenopausal Womena
Table 3.  
Stratified Analyses for the Association of Baseline Body Mass Index and WC Status With All-Cause Mortalitya,b
Stratified Analyses for the Association of Baseline Body Mass Index and WC Status With All-Cause Mortalitya,b
Table 4.  
Stratified Analyses for the Association of Baseline Body Mass Index and WC Status With Cardiovascular Disease Mortalitya,b
Stratified Analyses for the Association of Baseline Body Mass Index and WC Status With Cardiovascular Disease Mortalitya,b
Table 5.  
Stratified Analyses for the Association of Baseline Body Mass Index and WC Status With Cancer Mortalitya,b
Stratified Analyses for the Association of Baseline Body Mass Index and WC Status With Cancer Mortalitya,b
1.
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.  J Am Coll Cardiol. 2014;63(25 pt B):2985-3023. doi:10.1016/j.jacc.2013.11.004PubMedGoogle ScholarCrossref
2.
National Institutes of Health; National Heart, Lung, and Blood Institute; North American Association for the Study of Obesity.  The Practical Guide: Identification, Evaluation, and Treatment of Overweight and Obesity in Adults. Bethesda, MD: National Institutes of Health; 2000.
3.
World Health Organization. Obesity and overweight: fact sheet. https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight. Accessed June 18, 2019.
4.
Dulloo  AG, Jacquet  J, Solinas  G, Montani  JP, Schutz  Y.  Body composition phenotypes in pathways to obesity and the metabolic syndrome.  Int J Obes (Lond). 2010;34(suppl 2):S4-S17. doi:10.1038/ijo.2010.234PubMedGoogle ScholarCrossref
5.
Zhang  C, Rexrode  KM, van Dam  RM, Li  TY, Hu  FB.  Abdominal obesity and the risk of all-cause, cardiovascular, and cancer mortality: sixteen years of follow-up in US women.  Circulation. 2008;117(13):1658-1667. doi:10.1161/CIRCULATIONAHA.107.739714PubMedGoogle ScholarCrossref
6.
Sahakyan  KR, Somers  VK, Rodriguez-Escudero  JP,  et al.  Normal-weight central obesity: implications for total and cardiovascular Mortality.  Ann Intern Med. 2015;163(11):827-835. doi:10.7326/M14-2525PubMedGoogle ScholarCrossref
7.
Mainous  AG  III, Tanner  RJ, Jo  A, Anton  SD.  Prevalence of prediabetes and abdominal obesity among healthy-weight adults: 18-year trend.  Ann Fam Med. 2016;14(4):304-310.PubMedGoogle ScholarCrossref
8.
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. doi:10.1016/S0197-2456(97)00078-0PubMedGoogle ScholarCrossref
9.
Centers for Disease Control and Prevention. Defining adult overweight and obesity. https://www.cdc.gov/obesity/adult/defining.html. Accessed June 13, 2019.
10.
Grundy  SM, Cleeman  JI, Daniels  SR,  et al; American Heart Association; National Heart, Lung, and Blood Institute.  Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement.  Circulation. 2005;112(17):2735-2752. doi:10.1161/CIRCULATIONAHA.105.169404PubMedGoogle ScholarCrossref
11.
Curb  JD, McTiernan  A, Heckbert  SR,  et al; WHI Morbidity and Mortality Committee.  Outcomes ascertainment and adjudication methods in the Women’s Health Initiative.  Ann Epidemiol. 2003;13(9)(suppl):S122-S128. doi:10.1016/S1047-2797(03)00048-6PubMedGoogle ScholarCrossref
12.
Chiuve  SE, Fung  TT, Rimm  EB,  et al.  Alternative dietary indices both strongly predict risk of chronic disease.  J Nutr. 2012;142(6):1009-1018. doi:10.3945/jn.111.157222PubMedGoogle ScholarCrossref
13.
Johnson-Kozlow  M, Rock  CL, Gilpin  EA, Hollenbach  KA, Pierce  JP.  Validation of the WHI brief physical activity questionnaire among women diagnosed with breast cancer.  Am J Health Behav. 2007;31(2):193-202. doi:10.5993/AJHB.31.2.8PubMedGoogle ScholarCrossref
14.
Chi  GC, Hajat  A, Bird  CE,  et al.  Individual and neighborhood socioeconomic status and the association between air pollution and cardiovascular disease.  Environ Health Perspect. 2016;124(12):1840-1847. doi:10.1289/EHP199PubMedGoogle ScholarCrossref
15.
World Health Organization. Waist Circumference and Waist-Hip Ratio: Report of a WHO Expert Consultation. https://apps.who.int/iris/bitstream/handle/10665/44583/9789241501491_eng.pdf;jsessionid=79BCDD70CCD6F93D28BFF2169D90E15B?sequence=1. Accessed June 13, 2019.
16.
Bea  JW, Thomson  CA, Wertheim  BC,  et al.  Risk of mortality according to body mass index and body composition among postmenopausal women.  Am J Epidemiol. 2015;182(7):585-596. doi:10.1093/aje/kwv103PubMedGoogle ScholarCrossref
17.
Chen  Z, Klimentidis  YC, Bea  JW,  et al.  Body mass index, waist circumference, and mortality in a large multiethnic postmenopausal cohort: results from the Women’s Health Initiative.  J Am Geriatr Soc. 2017;65(9):1907-1915. doi:10.1111/jgs.14790PubMedGoogle ScholarCrossref
18.
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. doi:10.1001/jama.2012.113905PubMedGoogle ScholarCrossref
19.
Aune  D, Sen  A, Prasad  M,  et al.  BMI and all cause mortality: systematic review and non-linear dose-response meta-analysis of 230 cohort studies with 3.74 million deaths among 30.3 million participants.  BMJ. 2016;353:i2156.PubMedGoogle ScholarCrossref
20.
Thomson  CA, Garcia  DO, Wertheim  BC,  et al.  Body shape, adiposity index, and mortality in postmenopausal women: findings from the Women’s Health Initiative.  Obesity (Silver Spring). 2016;24(5):1061-1069. doi:10.1002/oby.21461PubMedGoogle ScholarCrossref
21.
Hamer  M, O’Donovan  G, Stensel  D, Stamatakis  E.  Normal-weight central obesity and risk for mortality.  Ann Intern Med. 2017;166(12):917-918. doi:10.7326/L17-0022PubMedGoogle ScholarCrossref
22.
Navab  M, Anantharamaiah  GM, Fogelman  AM.  The role of high-density lipoprotein in inflammation.  Trends Cardiovasc Med. 2005;15(4):158-161. doi:10.1016/j.tcm.2005.05.008PubMedGoogle ScholarCrossref
23.
Després  JP.  Intra-abdominal obesity: an untreated risk factor for type 2 diabetes and cardiovascular disease.  J Endocrinol Invest. 2006;29(3)(suppl):77-82.PubMedGoogle Scholar
24.
Arcidiacono  B, Iiritano  S, Nocera  A,  et al.  Insulin resistance and cancer risk: an overview of the pathogenetic mechanisms.  Exp Diabetes Res. 2012;2012:789174. doi:10.1155/2012/789174PubMedGoogle ScholarCrossref
25.
Harvie  M, Hooper  L, Howell  AH.  Central obesity and breast cancer risk: a systematic review.  Obes Rev. 2003;4(3):157-173. doi:10.1046/j.1467-789X.2003.00108.xPubMedGoogle ScholarCrossref
26.
Dong  Y, Zhou  J, Zhu  Y,  et al.  Abdominal obesity and colorectal cancer risk: systematic review and meta-analysis of prospective studies.  Biosci Rep. 2017;37(6):BSR20170945. doi:10.1042/BSR20170945PubMedGoogle ScholarCrossref
27.
Caan  BJ, Meyerhardt  JA, Kroenke  CH,  et al.  Explaining the obesity paradox: the association between body composition and colorectal cancer survival (C-SCANS Study).  Cancer Epidemiol Biomarkers Prev. 2017;26(7):1008-1015. doi:10.1158/1055-9965.EPI-17-0200PubMedGoogle ScholarCrossref
28.
Caan  BJ, Cespedes Feliciano  EM, Prado  CM,  et al.  Association of muscle and adiposity measured by computed tomography with survival in patients with nonmetastatic breast cancer.  JAMA Oncol. 2018;4(6):798-804. doi:10.1001/jamaoncol.2018.0137PubMedGoogle ScholarCrossref
29.
Srikanthan  P, Karlamangla  AS.  Muscle mass index as a predictor of longevity in older adults.  Am J Med. 2014;127(6):547-553. doi:10.1016/j.amjmed.2014.02.007PubMedGoogle ScholarCrossref
30.
Srikanthan  P, Horwich  TB, Tseng  CH.  Relation of muscle mass and fat mass to cardiovascular disease mortality.  Am J Cardiol. 2016;117(8):1355-1360. doi:10.1016/j.amjcard.2016.01.033PubMedGoogle ScholarCrossref
31.
Li  R, Xia  J, Zhang  XI,  et al.  Associations of muscle mass and strength with all-cause mortality among US older adults.  Med Sci Sports Exerc. 2018;50(3):458-467. doi:10.1249/MSS.0000000000001448PubMedGoogle ScholarCrossref
32.
Manolopoulos  KN, Karpe  F, Frayn  KN.  Gluteofemoral body fat as a determinant of metabolic health.  Int J Obes (Lond). 2010;34(6):949-959. doi:10.1038/ijo.2009.286PubMedGoogle ScholarCrossref
33.
Caan  BJ, Cespedes Feliciano  EM, Kroenke  CH.  The importance of body composition in explaining the overweight paradox in cancer-counterpoint.  Cancer Res. 2018;78(8):1906-1912. doi:10.1158/0008-5472.CAN-17-3287PubMedGoogle ScholarCrossref
34.
Wannamethee  SG, Shaper  AG, Whincup  PH, Lennon  L, Papacosta  O, Sattar  N.  The obesity paradox in men with coronary heart disease and heart failure: the role of muscle mass and leptin.  Int J Cardiol. 2014;171(1):49-55. doi:10.1016/j.ijcard.2013.11.043PubMedGoogle ScholarCrossref
35.
Lavie  CJ, McAuley  PA, Church  TS, Milani  RV, Blair  SN.  Obesity and cardiovascular diseases: implications regarding fitness, fatness, and severity in the obesity paradox.  J Am Coll Cardiol. 2014;63(14):1345-1354. doi:10.1016/j.jacc.2014.01.022PubMedGoogle ScholarCrossref
36.
Lavie  CJ, Alpert  MA, Arena  R, Mehra  MR, Milani  RV, Ventura  HO.  Impact of obesity and the obesity paradox on prevalence and prognosis in heart failure.  JACC Heart Fail. 2013;1(2):93-102. doi:10.1016/j.jchf.2013.01.006PubMedGoogle ScholarCrossref
Limit 200 characters
Limit 25 characters
Conflicts of Interest Disclosure

Identify all potential conflicts of interest that might be relevant to your comment.

Conflicts of interest comprise financial interests, activities, and relationships within the past 3 years including but not limited to employment, affiliation, grants or funding, consultancies, honoraria or payment, speaker's bureaus, stock ownership or options, expert testimony, royalties, donation of medical equipment, or patents planned, pending, or issued.

Err on the side of full disclosure.

If you have no conflicts of interest, check "No potential conflicts of interest" in the box below. The information will be posted with your response.

Not all submitted comments are published. Please see our commenting policy for details.

Limit 140 characters
Limit 3600 characters or approximately 600 words
    3 Comments for this article
    EXPAND ALL
    Underlying cause of normal-weight central "obesity"
    Diane Browning, BBA |
    It would be interesting to know how many of the “normal-weight with central obesity” women had undergone hysterectomy. 45% of U.S. women end up having one although less than 8% are done for a cancer diagnosis.(1)

    Hysterectomy (with or without ovary removal / oophorectomy) alters a woman’s figure such that her midsection becomes shorter and thicker (central “obesity”). This occurs because the uterine ligaments are the pelvis’ support structures that keep the spine, hips and rib cage in their rightful positions. When those support structures are severed to remove the uterus, the torso collapses. The ensuing widening of
    the hip bones and descent of the rib cage leads to, besides the aforementioned figure changes, back, hip and leg problems and reduced mobility.

    Hysterectomy (without ovary removal) has been shown to increase risk of a number of health problems including cardiovascular disease (2,3), some cancers - renal cell (4), rectal (5), thyroid (6,7), and metabolic morbidity (8).

    Therefore, one has to question if “normal-weight with obesity” is the underlying cause of the mortality risk or if it is hysterectomy.

    1 Stewart EA, Shuster LT, Rocca WA. Reassessing hysterectomy. Minn Med. 2012;95(3):36–39.
    2 Centerwall BS. Premenopausal hysterectomy and cardiovascular disease. Am J Obstet Gynecol. 1981 Jan;139(1):58-61.
    3 Laughlin-Tommaso SK, Khan Z, Weaver AL, Smith CY, Rocca WA, Stewart EA. Cardiovascular and metabolic morbidity after hysterectomy with ovarian conservation: a cohort study. Menopause. 2018;25(5):483–492. doi:10.1097/GME.0000000000001043
    4 Altman D, Yin L, Johansson A, Lundholm C, Grönberg H. Risk of Renal Cell Carcinoma After Hysterectomy. Arch Intern Med. 2010;170(22):2011–2016. doi:10.1001/archinternmed.2010.425
    5 Luoto R1, Auvinen A, Pukkala E, Hakama M. Hysterectomy and subsequent risk of cancer. Int J Epidemiol. 1997 Jun;26(3):476-83.
    6 Luoto R1, Auvinen A, Pukkala E, Hakama M. Hysterectomy and subsequent risk of cancer.
    7 Luo J, Hendryx M, Manson JE, Liang X, Margolis KL. Hysterectomy, Oophorectomy, and Risk of Thyroid Cancer. J Clin Endocrinol Metab. 2016;101(10):3812–3819. doi:10.1210/jc.2016-2011
    8 Laughlin-Tommaso SK, Khan Z, Weaver AL, Smith CY, Rocca WA, Stewart EA. Cardiovascular and metabolic morbidity after hysterectomy with ovarian conservation: a cohort study.
    CONFLICT OF INTEREST: None Reported
    READ MORE
    NAFLD/NASH: Another Important Comorbidity of Central Obesity
    Cathleen Dohrn, PhD | Continuum Clinical
    This study showed a relationship between post-menopausal central obesity and CVD, as well as cancer. It concludes that guidelines are needed to prevent and control post-menopausal women with normal weight and central obesity but does not go far enough in addressing other key concerns for this population.

    There are other diseases that are associated with central obesity that could be included in the guidelines. It is well accepted that Type 2 diabetes and metabolic syndrome are more prevalent in patients with central obesity. Central, or visceral, obesity is also implicated in the related disease non-alcoholic fatty liver
    disease (NAFLD), which can progress to non-alcoholic steatohepatitis (NASH). Based on the results in this study, it follows that post-menopausal women are not only at a higher risk for CVD, but also NAFLD/NASH because of the higher rate of central obesity in this population.

    1. Tyrovolas et al., Experimental Gerontology, 2015: 64:70-77
    2. Bellentani, Liver International, 2017:37 (Suppl. 1): 81-84
    3. Farrell and Larter, Hepatology, 2006:43 (No. 2, Suppl. 1: S99-S112
    CONFLICT OF INTEREST: Continuum Clinical employee.
    READ MORE
    Waist Hip Ratio as useful risk factor
    Arthur Hartz, PhD, MD and Alfred Rimm, PhD | Case WesternReserve University School of Medicine
    The analysis of Sun et al[1] of Women’s Health Initiative (WHI) data showed that waist circumference (WC) was independent of body mass index (BMI) as a risk factor for mortality from all causes, cardiovascular diseases, and cancer. In 2011 we published a similar analysis of the WHI data[2] that found that waist circumference was independent of BMI as a risk factor for all-cause mortality, diabetes, hypertension, gall bladder disease, and stroke.

    One difference between our study and Sun et al study was that we also included as a risk factor the ratio of waist circumference
    to hip circumference (WHR). Although WHR is a weaker single risk factor than WC, it is less associated with BMI. After adjusting for BMI and many other variables the risks of several conditions were more strongly associated with WHR than with WC as indicated by higher chi-squared values for the same condition in the same sample. These conditions with the chi-squared values for WHR and WC were 1) diabetes at baseline (2364 vs 1788), 2) incident diabetes (2204 vs 1395), 3) hypertension at baseline (1752 vs 1193), 4) systolic blood pressure in those untreated for hypertension (624 vs 395), 5) MI during follow-up (132 vs 112), and 6) stroke during follow-up (45 vs 34).

    A way of showing the clinical importance of WHR is to compare the highest WHR quintile and highest WC quintile for the risk of current diabetes among normal weight women. Since almost all high WC women were overweight or obese, there were 23 times as many normal weight women with high WHR as with high WC (3213 vs 139). The adjusted hazard ratios (compared to women in the lowest quintile) among normal weight women were about 3.9 for high WHR and 2.4 for high WC. Our results suggest that WHR might be a useful risk factor for cardiovascular mortality although we did not test this.

    Neither WC or WHR are new risk factors. We introduced both of them at conferences in 1980[3,4] and since 1983[3]have published many articles in reputable journals. The major conclusions of all of these articles are that WC is a stronger risk factor than BMI for many diseases, and that WHR adds more information than WC to BMI. We don’t know if WHR would have been a useful risk factor in the Sun et al. study. It should have been considered.

    1. Sun Y, Liu B, Snetselaar LG et al Association of Normal-Weight Central Obesity With All-Cause and Cause-Specific Mortality Among Postmenopausal Women. JAMA Network Open.. 2019;2(7):e197337. doi:10.1001/jamanetworkopen.2019.7337
    2. Hartz AJ, He T, Rimm AR. Comparison of Adiposity Measures as Risk Factors in Post-Menopausal Women. The Journal of Clinical Endocrinology & Metabolism (2012) 97(1): 227–233.
    3. Hartz AJ, Rupley DC Jr, Kalkhoff RD, Rimm AA. Relationship of obesity to diabetes: influence of obesity level and body fat distribution. Prev Med. (1983); 12(2): 351-357.
    4. Hartz AJ, Rupley DC, Kissebah AH, Kalkhoff RK, Rimm AA. Relationship of Obesity to Diabetes: Influence of Obesity Level and Body Fat Distribution. Third International Congress on Obesity, October 10, 1980.
    5. Rimm A, Hartz AJ, Rupley D Jr et al. Body shape overweight as distinct risk factors for diabetes (abstract) Am J Epidemiol 1980; 112(3):446
    CONFLICT OF INTEREST: None Reported
    READ MORE
    Original Investigation
    Nutrition, Obesity, and Exercise
    July 24, 2019

    Association of Normal-Weight Central Obesity With All-Cause and Cause-Specific Mortality Among Postmenopausal Women

    Author Affiliations
    • 1Department of Epidemiology, College of Public Health, University of Iowa, Iowa City
    • 2Division of Research, Kaiser Permanente Northern California, Oakland
    • 3Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York
    • 4Cancer Prevention Program, Fred Hutchinson Cancer Research Center, Seattle, Washington
    • 5Department of Family Medicine and Public Health, School of Medicine, University of California, San Diego, La Jolla
    • 6Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center Duarte, Duarte, California
    • 7Division of Preventive Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
    • 8Obesity Research and Education Initiative, University of Iowa, Iowa City
    • 9Fraternal Order of Eagles Diabetes Research Center, University of Iowa, Iowa City
    JAMA Netw Open. 2019;2(7):e197337. doi:10.1001/jamanetworkopen.2019.7337
    Key Points español 中文 (chinese)

    Question  How is normal-weight central obesity associated with risk of mortality compared with other anthropometric phenotypes?

    Findings  In this cohort study of 156 624 postmenopausal US women enrolled in the Women’s Health Initiative study, normal-weight central obesity was associated with higher risk of all-cause, cardiovascular disease, and cancer mortality compared with normal weight without central obesity. The magnitude of this association was similar to that of obesity with central obesity and higher than that of other anthropometric phenotypes defined by body mass index and waist circumference.

    Meaning  Normal-weight central obesity is an underrecognized, high-risk phenotype for mortality.

    Abstract

    Importance  Current public health guidelines for obesity prevention and control focus on promoting a normal body mass index (BMI), rarely addressing central obesity, which is reflected by high waist circumference (WC) and common in the general population. Studies of the association of normal-weight central obesity with long-term health outcomes are sparse.

    Objective  To examine associations of normal-weight central obesity with all-cause and cause-specific mortality in postmenopausal women in the United States.

    Design, Setting, and Participants  A nationwide prospective cohort study of 156 624 postmenopausal women enrolled in the Women’s Health Initiative at 40 clinical centers in the United States between 1993 and 1998. These women were observed through February 2017. Data analysis was performed from September 15, 2017, to March 13, 2019.

    Exposures  Different combinations of BMI (calculated as weight in kilograms divided by height in meters squared; normal weight: BMI, 18.5-24.9; overweight: BMI, 25.0-29.9; and obesity: BMI, ≥30) and WC (normal: WC, ≤88 cm and high: WC, >88 cm).

    Main Outcomes and Measures  Mortality from all causes, cardiovascular disease, and cancer.

    Results  Of the 156 624 women (mean [SD] age, 63.2 [7.2] years), during 2 811 187 person-years of follow-up, 43 838 deaths occurred, including 12 965 deaths from cardiovascular disease (29.6%) and 11 828 deaths from cancer (27.0%). Compared with women with normal weight and no central obesity and adjusted for demographic characteristics, socioeconomic status, lifestyle factors, and hormone use, the hazard ratio for all-cause mortality was 1.31 (95% CI, 1.20-1.42) among women with normal weight and central obesity, 0.91 (95% CI, 0.89-0.94) among women with overweight and no central obesity, 1.16 (95% CI, 1.13-1.20) for women with overweight and central obesity, 0.93 (95% CI, 0.89-0.94) for women with obesity and no central obesity, and 1.30 (95% CI, 1.27-1.34) for women with obesity and central obesity. Compared with normal weight without central obesity, normal-weight central obesity was associated with higher risk of cardiovascular disease mortality (hazard ratio, 1.25; 95% CI, 1.05-1.46) and cancer mortality (hazard ratio, 1.20; 95% CI, 1.01-1.43).

    Conclusions and Relevance  Normal-weight central obesity in women was associated with excess risk of mortality, similar to that of women with BMI-defined obesity with central obesity. These findings underscore the need for future public health guidelines to include the prevention and control of central obesity, even in individuals with normal BMI.

    Introduction

    Although body mass index (BMI, calculated as weight in kilograms divided by height in meters squared) is the standard measure used to define obesity in clinical and public health guidelines,1-3 an inherent limitation is that BMI does not distinguish body shape or body fat distribution.4 Central obesity, characterized by relatively high abdominal fat distribution, has been associated with higher risk of mortality, independent of BMI.5 Even among individuals with normal weight (BMI, <25.0), those with central obesity may be at increased risk of mortality because of excessive abdominal fat accumulation.6 However, individuals who have normal BMI with central obesity are usually neglected in clinical guidelines. In the most recent obesity management guidelines by the American Heart Association, the American College of Cardiology, and the Obesity Society,1 measuring central obesity was recommended among people who have overweight or class I obesity (BMI, 25.0-34.9) but not among people of normal weight owing to lack of available evidence regarding risk evaluation in this group. Moreover, individuals with normal-weight central obesity receive little attention in the setting of risk reduction strategies, such as lifestyle modifications and other interventions. Because central obesity is common among US adults, including those with normal BMI,7 it is important to evaluate long-term health risks among people with normal weight and central obesity.

    Our hypothesis was that women with normal weight (defined by BMI) and central obesity (defined by waist circumference [WC]) and women with other BMI/WC combinations were at higher risk of mortality compared with women with normal weight and no central obesity. We examined associations of different combinations of BMI and central obesity with all-cause and cause-specific mortality and assessed the magnitude of risk from normal weight with central obesity by comparing it with the risk from other combinations of BMI and central obesity in a large, prospective cohort of postmenopausal women in the United States.

    Methods
    Study Population

    The Women’s Health Initiative (WHI) study design has been previously described in detail.8 Briefly, between 1993 and 1998, postmenopausal women aged 50 to 79 years at study entry were recruited through 40 clinical centers into either a randomized clinical trial (RCT) component (n = 68 132) or an observational study (OS) component (n = 93 676 women). The RCTs consisted of 4 trials including 1 dietary modification trial, 2 hormonal therapy trials, and 1 calcium and vitamin D trial. The RCTs and OS were closed between 2004 and 2005, and participants were invited to continue being observed in the WHI Extension Study, which currently has follow-up data through February 2017. In the present study, we included participants in the RCT and OS components. Written informed consent was obtained from each participant. Institutional review board approval was obtained from all participating institutions. The present study was performed and reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for cohort studies.

    Anthropometric Measures

    Height, weight, and WC were measured in the study clinic at baseline.8 Weight was measured to the nearest 0.1 kg on a balance beam scale with the participant dressed in indoor clothing without shoes. Height was measured to the nearest 0.1 cm using a wall-mounted stadiometer. Trained staff at each WHI clinic used tape measures to measure WC at the natural waist or narrowest part of the torso to the nearest 0.5 cm.

    Body mass index was classified as follows: (1) normal weight, BMI from 18.5 to 24.9; (2) overweight, BMI from 25.0 to 29.9; and (3) obesity, BMI 30.0 or more.9 Central obesity was defined as WC higher than 88 cm.10 Obesity patterns were categorized into 6 groups on the basis of combinations of BMI and WC categories as follows: (1) normal weight without central obesity (BMI, 18.5-24.9; WC, ≤88 cm), (2) normal weight with central obesity (BMI, 18.5-24.9; WC, >88 cm), (3) overweight without central obesity (BMI, 25.0-29.9; WC, ≤88 cm), (4) overweight with central obesity (BMI, 25.0-29.9; WC, >88 cm), (5) obese without central obesity (BMI, ≥30.0; WC, ≤88 cm), and (6) obese with central obesity (BMI, ≥30.0; WC, >88 cm).

    Ascertainment of Death

    Mortality end points for this study included all-cause mortality (primary outcome), cardiovascular disease (CVD) mortality, and cancer mortality. Death from CVD included death from all diseases of the circulatory system (International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes I00-I99). Death from cancer included death from all cancer (codes C01 to C99). Deaths were ascertained by review of medical records and death certificates at the WHI Clinical Coordinating Center and by linkage to the National Death Index.11 All adjudicators were masked to RCT randomization assignment. Ascertainment of outcomes was complete as of February 28, 2017.

    Other Covariate Assessments

    Information on demographic characteristics (ie, age, race/ethnicity), individual socioeconomic status (ie, education level, annual income), and lifestyle (ie, smoking status, physical activity, alcohol intake, total energy intake, overall diet quality, and past hormone use [ie, unopposed estrogen use and estrogen plus progestin use]) was collected at baseline through self-reports. Overall diet quality was indicated by the Alternative Healthy Eating Index 2010,12 scored on the basis of the intake of 11 components including vegetables, fruit, whole grains, sugar-sweetened beverages and fruit juices, nuts and legumes, red/processed meat, trans fat, long-chain (omega-3) fats (ie, eicosapentaenoic acid and docosahexaenoic acid), polyunsaturated fatty acids, sodium consumption, and alcohol consumption. Recreational moderate to vigorous intensity physical activity, including walking, was assessed by questionnaire, and metabolic equivalent of task hours per week of recreational physical activity were calculated for each participant.8,13 Neighborhood socioeconomic status (NSES) was assessed by using data from the 2000 US Census at the census tract level, as described in previous publications.14 The NSES index was scaled to range from 0 to 100 for census tracts; higher scores indicated more affluent tracts. When categorizing each categorical covariate, we created a category for missing data where needed.

    Statistical Analysis

    Comparisons of covariates among different groups of women with different combinations of BMI and WC were performed using analysis of variance for continuous variables and χ2 test for categorical variables. Cox proportional hazards regression models were used to estimate hazard ratios (HRs) and 95% CIs for risk of all-cause mortality associated with different BMI/WC patterns and cause-specific hazard models for risk of cause-specific mortality. Person-years were calculated from the date of the anthropometric measurement at baseline until death, the last National Death Index search date, or the follow-up through February 28, 2017, whichever came first. Multivariable models were constructed in several stages. Model 1 was adjusted for age at baseline and race/ethnicity. Model 2 was additionally adjusted for education level, annual income, WHI component (ie, RCT or OS), NSES (in quartiles), unopposed estrogen use, and estrogen plus progestin use. Model 3 was additionally adjusted for smoking status, physical activity, alcohol intake, total energy intake (in quartiles), and score on the Alternative Healthy Eating Index 2010 (in quartiles).

    We evaluated if the associations varied by age (<65 vs ≥65 years), race/ethnicity (white vs black, Hispanic, American Indian/Alaskan Native, Asian/Pacific Islander, or other), education (<college vs ≥college), annual income (<$50 000 vs ≥$50 000), smoking status (never smoked vs ever smoked), physical activity (metabolic equivalent of task hours per week, <10 vs ≥10), diet quality (Alternative Healthy Eating Index 2010 score, ≤50 vs >50), NSES (≤75 vs >75), unopposed estrogen use (never used vs ever used), and estrogen plus progestin use (never used vs ever used). We first conducted interaction tests via multiplicative interaction terms in the multivariable models, and when significant interactions were detected, we showed data in different strata. In sensitivity analyses, we repeated the analyses by (1) excluding women from RCTs; (2) restricting the analysis to white women; and (3) excluding women with major comorbidities at baseline (eTables 1-3 in the Supplement). We performed additional analysis by using waist-to-hip ratio of 0.85 or higher to define central obesity.15

    All statistical analyses were conducted using SAS version 9.4 (SAS Institute). All statistical tests were based on prespecified hypotheses, and therefore, there was no adjustment for multiple testing. All tests were 2-sided with statistical significance set at P < .05.

    Results

    Of participants in the WHI RCT (n = 68 132) and OS (n = 93 676) components, 159 792 women (RCT, 67 584 [99.2%]; OS, 92 208 [98.4%]) had information on BMI and WC. We excluded 1393 women who had BMI lower than 18.5 and 1775 women who died within 3 years of the baseline visit, leaving 156 624 women in the final study cohort (RCT, 66 674 [42.6%]; OS, 89 950 [57.4%]).

    Of the 156 624 women (mean [SD] age, 63.2 [7.2] years) included in this study, 1390 had normal-weight central obesity, accounting for 0.9% among all women and 2.6% among women with normal weight. During the 2 811 187 person-years of follow up, 43 838 deaths occurred, including 12 965 deaths from CVD (29.6%), 11 828 deaths from cancer (27.0%), and 19 045 deaths from other causes (43.4%). Across BMI categories, women with central obesity were more likely than women without central obesity to be older and nonwhite, with less education, lower income, and lower NSES compared with women without central obesity (Table 1). Women with central obesity were more likely than women without central obesity to be participants from the WHI RCTs, noncurrent users of hormones, and current smokers and to have lower physical activity levels, higher total energy intake, and lower diet quality.

    After adjustment for demographic characteristics, NSES, lifestyle factors, and hormone use, women with central obesity in each BMI category were at increased risk of all-cause mortality compared with women with normal weight and no central obesity, while women with overweight or obesity and no central obesity were at a slightly lower risk of all-cause mortality (Table 2). The HRs for all-cause mortality were 1.31 (95% CI, 1.20-1.42; P < .001) among women with normal weight and central obesity, 1.16 (95% CI, 1.13-1.20; P < .001) among women with overweight and central obesity, and 1.30 (95% CI, 1.27-1.34; P < .001) among women with obesity and central obesity. It is notable that women with normal-weight central obesity had a similar risk as women with obesity and central obesity, and the risk was 13% to 44% higher than among women with any other BMI/WC combination, including women with overweight and no central obesity (HR, 0.91; 95% CI, 0.89-0.94; P < .001) and women with obesity and no central obesity (HR, 0.93; 95% CI, 0.87-0.99; P = .01). Results of defining central obesity as waist-hip ratio of 0.85 or larger were largely similar. The corresponding HRs were 1.33 (95% CI, 1.27-1.39) for normal weight women with central obesity compared with normal weight women without central obesity (eTable 4 in the Supplement). Patterns for CVD, cancer, and non-CVD/noncancer mortality were similar. Women with normal weight and central obesity had a higher risk of cardiovascular disease (HR, 1.24; 95% CI, 1.05-1.46) and cancer mortality (HR, 1.20; 95% CI, 1.01-1.43) compared with women with normal weight and no central obesity.

    Associations of different BMI/WC combinations with all-cause, CVD, and cancer mortality were generally similar across categories of age, race/ethnicity, education, income, NSES, diet quality, smoking status, physical activity, unopposed estrogen use, and estrogen plus progestin use, except that the magnitudes of risk were greater for all-cause mortality among younger women (aged <65 years) (Table 3), for CVD mortality among younger women (aged <65 years) and women with higher diet quality (Table 4), and for cancer mortality among women with lower physical activity levels, women with higher diet quality, and women with lower NSES (Table 5). The results were robust in our sensitivity analyses when we restricted to women from the OS component to avoid changes in risk factor status related to the RCT interventions (eTable 1 in the Supplement), when analyses were limited to white women (eTable 2 in the Supplement), and when women with major comorbidities at baseline were excluded (eTable 3 in the Supplement).

    Discussion

    In this large prospective cohort study among postmenopausal women with long-term follow-up, women with normal weight and central obesity had an elevated risk of all-cause mortality, similar to the risk among women with obesity and central obesity and higher than the risk among women with any other combination of BMI and WC. Women with normal-weight central obesity had the second highest risk of CVD mortality, with women with obesity and central obesity having the greatest risk.

    Although several previous studies have investigated associations of BMI and WC, either separately or in combination, with mortality risk,16-20 very few studies have evaluated the risk of mortality among people with normal-weight central obesity or the magnitude of the risk.6,21 Our results are generally consistent with those of a study using data from the National Health and Nutrition Examination Survey (NHANES) III that showed that among 7249 women, those with normal-weight central obesity had an elevated risk of all-cause mortality, similar in magnitude to the risk among women with obesity and central obesity.6 The risk of CVD mortality among women with normal-weight central obesity compared with women with other obesity patterns in the NHANES study were unclear. Similar results were observed in a UK study among 42 702 participants.21 However, neither the NHANES study nor the UK study investigated the association of normal-weight central obesity with cancer mortality. To our knowledge, our study is the largest study with the longest follow-up period investigating the association of normal-weight central obesity with all-cause and CVD mortality and the first study to report the association of normal-weight central obesity with cancer mortality.

    There are several explanations for our findings showing that women with normal-weight central obesity were at higher risk of all-cause, CVD, and cancer mortality. First, the adverse effect of visceral fat and the lack of protective effect of muscle mass owing to this combination of BMI and WC may be an explanation. Body mass index is a measure of both fat and fat-free mass, while WC is a measure of abdominal fat accumulation. Individuals with normal weight and a high WC may have excessive visceral fat, and their normal BMI may put them at risk for less muscle mass than counterparts with the same BMI and no central obesity. Previous studies have shown that excessive visceral fat is associated with insulin resistance, hyperinsulinemia, dyslipidemia, and inflammation, which are risk factors for CVD and several types of cancer, including breast cancer and colon cancer.22-28 In contrast, muscle mass is associated with a more favorable metabolic profile, and the lack of muscle mass could lead to the loss of its protective association with adverse health outcomes.29-31 Second, higher WC with normal BMI could suggest decreased subcutaneous fat on hips and legs for a given amount of visceral fat. The presence of gluteofemoral adipose tissue has been linked to an improved metabolic and cardiovascular risk profile, owing to differential regulation of lower-body fatty acid release and uptake at the level of the adipocyte and resulting in the long-term entrapment of fatty acids in this depot and protection from ectopic fat accumulation.32 Thus, a decrease in the protective gluteofemoral adipose tissue among women with normal-weight central obesity could lead to poor overall survival. On the contrary, women with overweight based on BMI may have a greater amount of gluteofemoral adipose tissue associated with an improved metabolic and cardiovascular risk profile, which could partially explain the obesity paradox.33-36

    Our findings have important clinical and public health implications. People with normal weight based on BMI, regardless of central obesity status, were generally considered normal in clinical practice according to current guidelines and policy makers. This could lead to a missed opportunity for risk evaluation and intervention programs for a high-risk but neglected subgroup (ie, those with normal-weight central obesity). In the most recent 2013 American Heart Association, American College of Cardiology, and the Obesity Society obesity management guideline,1 measuring waist circumference was recommended only in people who have either overweight or class I obesity (BMI, 25.0-34.9) but not among people with normal weight owing to lack of available evidence regarding risk evaluation in this group. This guideline may send the public and clinical professionals a message that people with normal BMI are free of any particular obesity-related risk, while, in fact, they were at an elevated risk of mortality and might need risk reduction programs, such as lifestyle modifications and other interventions.

    Strengths and Limitations

    Our study has several strengths, including the large sample size, the prospective study design, which can establish the temporal direction of the associations, and long-term follow-up. Additionally, we had detailed data on confounders that could potentially alter the associations of BMI/WC combinations with risk of mortality; therefore, we could explore the joint associations of BMI and WC comprehensively. Furthermore, the anthropometric measures were taken directly by trained staff instead of through self-reporting. Last, measurements of BMI and WC are widely available and feasible; thus, our results may be applicable to clinical settings worldwide.

    We acknowledge that there are several limitations. First, because our participants were older postmenopausal women, our findings may not apply to women at younger age, premenopausal and perimenopausal women, or men. Second, imaging data of adipose tissue was not available for all WHI participants. Therefore, information on body fat distribution was based on anthropometric measures, such as WC, which may be difficult to measure and less accurate in individuals with a BMI of 35 or higher. However, even though it is an indirect measure of abdominal fat, WC has been shown to be associated with risk of death from CVD, cancer, and other causes.5 Furthermore, WC has advantages as an easier, more convenient, and less expensive measure, and therefore, measuring WC is much more feasible in practice than expensive body imaging modalities. Third, the cutoff points of BMI from 25.0 to 29.9 to define overweight and BMI of 30.0 and higher to define obesity might not be appropriate for all nonwhite people. However, most participants in our study were white women, and the results were similar in a sensitivity analysis when we restricted to white participants only. Fourth, we only used baseline exposure data, which could not account for the effect of changes in exposure on outcome.

    Conclusions

    This large prospective cohort study found that women with normal-weight central obesity were at higher risk of mortality compared with women with normal weight and no central obesity. Women with normal weight and central obesity were at comparable risk as women with BMI-defined obesity and central obesity. Our results highlight the inability of BMI alone to distinguish body shape or body fat distribution, the misclassification of risk because of adiposity that occurs when using BMI as a proxy for fat mass, and the importance of measuring central obesity even among people with normal weight. Furthermore, our results demonstrated that WC can be used in combination with BMI to better stratify patients for mortality risk. Future research is needed to develop and test the effectiveness of interventions to reduce risk owing to excess body fat among people with normal-weight central obesity. Our findings challenge the current paradigm that measurement of abdominal fat is not recommended for individuals with normal BMI.

    Back to top
    Article Information

    Accepted for Publication: May 24, 2019.

    Published: July 24, 2019. doi:10.1001/jamanetworkopen.2019.7337

    Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2019 Sun Y et al. JAMA Network Open.

    Corresponding Author: Wei Bao, MD, PhD, Department of Epidemiology, College of Public Health, University of Iowa, 145 N Riverside Dr, Room S431 CPHB, Iowa City, IA 52242 (wei-bao@uiowa.edu).

    Author Contributions: Drs Sun and Bao 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.

    Concept and design: Sun, Caan, Manson, Bao.

    Acquisition, analysis, or interpretation of data: All authors.

    Drafting of the manuscript: Sun, Wallace, Caan.

    Critical revision of the manuscript for important intellectual content: All authors.

    Statistical analysis: Sun, Caan.

    Obtained funding: Wallace, Caan, Chlebowski.

    Administrative, technical, or material support: Sun, Wallace, Caan, Neuhouser, Manson, Bao.

    Supervision: Snetselaar, Caan, Neuhouser, Chlebowski, Bao.

    Other: Shadyab.

    Conflict of Interest Disclosures: Dr Chlebowski reported receiving grants through the National Institutes of Health, National Cancer Institute, and American Institute of Cancer Research during the conduct of this study and receiving personal fees from Novartis, AstraZeneca, Genentech, Amgen, Genomic Health, and Immunomedics outside the submitted work. Dr Manson reported grants from the National Institutes of Health during the conduct of the study and outside the submitted work. No other disclosures were reported.

    Funding/Support: The Women’s Health Initiative (WHI) program is funded through contracts HHSN268201600018C, HHSN268201600001C, HHSN268201600002C, HHSN268201600003C, and HHSN268201600004C from the National Heart, Lung, and Blood Institute, the National Institutes of Health, and the US Department of Health and Human Services.

    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. This article was prepared in collaboration with investigators of the WHI and has been reviewed and/or approved by the WHI.

    Additional Contributions: We acknowledge the dedicated efforts of investigators and staff at WHI clinical centers, the WHI Clinical Coordinating Center, and the National Heart, Lung and Blood program office (https://www.whi.org). We also recognize the WHI participants for their extraordinary commitment to the WHI program. For a list of all the investigators who have contributed to WHI science, visit http://www.whiscience.org/wp-content/uploads/WHI_investigators_longlist.pdf.

    References
    1.
    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.  J Am Coll Cardiol. 2014;63(25 pt B):2985-3023. doi:10.1016/j.jacc.2013.11.004PubMedGoogle ScholarCrossref
    2.
    National Institutes of Health; National Heart, Lung, and Blood Institute; North American Association for the Study of Obesity.  The Practical Guide: Identification, Evaluation, and Treatment of Overweight and Obesity in Adults. Bethesda, MD: National Institutes of Health; 2000.
    3.
    World Health Organization. Obesity and overweight: fact sheet. https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight. Accessed June 18, 2019.
    4.
    Dulloo  AG, Jacquet  J, Solinas  G, Montani  JP, Schutz  Y.  Body composition phenotypes in pathways to obesity and the metabolic syndrome.  Int J Obes (Lond). 2010;34(suppl 2):S4-S17. doi:10.1038/ijo.2010.234PubMedGoogle ScholarCrossref
    5.
    Zhang  C, Rexrode  KM, van Dam  RM, Li  TY, Hu  FB.  Abdominal obesity and the risk of all-cause, cardiovascular, and cancer mortality: sixteen years of follow-up in US women.  Circulation. 2008;117(13):1658-1667. doi:10.1161/CIRCULATIONAHA.107.739714PubMedGoogle ScholarCrossref
    6.
    Sahakyan  KR, Somers  VK, Rodriguez-Escudero  JP,  et al.  Normal-weight central obesity: implications for total and cardiovascular Mortality.  Ann Intern Med. 2015;163(11):827-835. doi:10.7326/M14-2525PubMedGoogle ScholarCrossref
    7.
    Mainous  AG  III, Tanner  RJ, Jo  A, Anton  SD.  Prevalence of prediabetes and abdominal obesity among healthy-weight adults: 18-year trend.  Ann Fam Med. 2016;14(4):304-310.PubMedGoogle ScholarCrossref
    8.
    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. doi:10.1016/S0197-2456(97)00078-0PubMedGoogle ScholarCrossref
    9.
    Centers for Disease Control and Prevention. Defining adult overweight and obesity. https://www.cdc.gov/obesity/adult/defining.html. Accessed June 13, 2019.
    10.
    Grundy  SM, Cleeman  JI, Daniels  SR,  et al; American Heart Association; National Heart, Lung, and Blood Institute.  Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement.  Circulation. 2005;112(17):2735-2752. doi:10.1161/CIRCULATIONAHA.105.169404PubMedGoogle ScholarCrossref
    11.
    Curb  JD, McTiernan  A, Heckbert  SR,  et al; WHI Morbidity and Mortality Committee.  Outcomes ascertainment and adjudication methods in the Women’s Health Initiative.  Ann Epidemiol. 2003;13(9)(suppl):S122-S128. doi:10.1016/S1047-2797(03)00048-6PubMedGoogle ScholarCrossref
    12.
    Chiuve  SE, Fung  TT, Rimm  EB,  et al.  Alternative dietary indices both strongly predict risk of chronic disease.  J Nutr. 2012;142(6):1009-1018. doi:10.3945/jn.111.157222PubMedGoogle ScholarCrossref
    13.
    Johnson-Kozlow  M, Rock  CL, Gilpin  EA, Hollenbach  KA, Pierce  JP.  Validation of the WHI brief physical activity questionnaire among women diagnosed with breast cancer.  Am J Health Behav. 2007;31(2):193-202. doi:10.5993/AJHB.31.2.8PubMedGoogle ScholarCrossref
    14.
    Chi  GC, Hajat  A, Bird  CE,  et al.  Individual and neighborhood socioeconomic status and the association between air pollution and cardiovascular disease.  Environ Health Perspect. 2016;124(12):1840-1847. doi:10.1289/EHP199PubMedGoogle ScholarCrossref
    15.
    World Health Organization. Waist Circumference and Waist-Hip Ratio: Report of a WHO Expert Consultation. https://apps.who.int/iris/bitstream/handle/10665/44583/9789241501491_eng.pdf;jsessionid=79BCDD70CCD6F93D28BFF2169D90E15B?sequence=1. Accessed June 13, 2019.
    16.
    Bea  JW, Thomson  CA, Wertheim  BC,  et al.  Risk of mortality according to body mass index and body composition among postmenopausal women.  Am J Epidemiol. 2015;182(7):585-596. doi:10.1093/aje/kwv103PubMedGoogle ScholarCrossref
    17.
    Chen  Z, Klimentidis  YC, Bea  JW,  et al.  Body mass index, waist circumference, and mortality in a large multiethnic postmenopausal cohort: results from the Women’s Health Initiative.  J Am Geriatr Soc. 2017;65(9):1907-1915. doi:10.1111/jgs.14790PubMedGoogle ScholarCrossref
    18.
    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. doi:10.1001/jama.2012.113905PubMedGoogle ScholarCrossref
    19.
    Aune  D, Sen  A, Prasad  M,  et al.  BMI and all cause mortality: systematic review and non-linear dose-response meta-analysis of 230 cohort studies with 3.74 million deaths among 30.3 million participants.  BMJ. 2016;353:i2156.PubMedGoogle ScholarCrossref
    20.
    Thomson  CA, Garcia  DO, Wertheim  BC,  et al.  Body shape, adiposity index, and mortality in postmenopausal women: findings from the Women’s Health Initiative.  Obesity (Silver Spring). 2016;24(5):1061-1069. doi:10.1002/oby.21461PubMedGoogle ScholarCrossref
    21.
    Hamer  M, O’Donovan  G, Stensel  D, Stamatakis  E.  Normal-weight central obesity and risk for mortality.  Ann Intern Med. 2017;166(12):917-918. doi:10.7326/L17-0022PubMedGoogle ScholarCrossref
    22.
    Navab  M, Anantharamaiah  GM, Fogelman  AM.  The role of high-density lipoprotein in inflammation.  Trends Cardiovasc Med. 2005;15(4):158-161. doi:10.1016/j.tcm.2005.05.008PubMedGoogle ScholarCrossref
    23.
    Després  JP.  Intra-abdominal obesity: an untreated risk factor for type 2 diabetes and cardiovascular disease.  J Endocrinol Invest. 2006;29(3)(suppl):77-82.PubMedGoogle Scholar
    24.
    Arcidiacono  B, Iiritano  S, Nocera  A,  et al.  Insulin resistance and cancer risk: an overview of the pathogenetic mechanisms.  Exp Diabetes Res. 2012;2012:789174. doi:10.1155/2012/789174PubMedGoogle ScholarCrossref
    25.
    Harvie  M, Hooper  L, Howell  AH.  Central obesity and breast cancer risk: a systematic review.  Obes Rev. 2003;4(3):157-173. doi:10.1046/j.1467-789X.2003.00108.xPubMedGoogle ScholarCrossref
    26.
    Dong  Y, Zhou  J, Zhu  Y,  et al.  Abdominal obesity and colorectal cancer risk: systematic review and meta-analysis of prospective studies.  Biosci Rep. 2017;37(6):BSR20170945. doi:10.1042/BSR20170945PubMedGoogle ScholarCrossref
    27.
    Caan  BJ, Meyerhardt  JA, Kroenke  CH,  et al.  Explaining the obesity paradox: the association between body composition and colorectal cancer survival (C-SCANS Study).  Cancer Epidemiol Biomarkers Prev. 2017;26(7):1008-1015. doi:10.1158/1055-9965.EPI-17-0200PubMedGoogle ScholarCrossref
    28.
    Caan  BJ, Cespedes Feliciano  EM, Prado  CM,  et al.  Association of muscle and adiposity measured by computed tomography with survival in patients with nonmetastatic breast cancer.  JAMA Oncol. 2018;4(6):798-804. doi:10.1001/jamaoncol.2018.0137PubMedGoogle ScholarCrossref
    29.
    Srikanthan  P, Karlamangla  AS.  Muscle mass index as a predictor of longevity in older adults.  Am J Med. 2014;127(6):547-553. doi:10.1016/j.amjmed.2014.02.007PubMedGoogle ScholarCrossref
    30.
    Srikanthan  P, Horwich  TB, Tseng  CH.  Relation of muscle mass and fat mass to cardiovascular disease mortality.  Am J Cardiol. 2016;117(8):1355-1360. doi:10.1016/j.amjcard.2016.01.033PubMedGoogle ScholarCrossref
    31.
    Li  R, Xia  J, Zhang  XI,  et al.  Associations of muscle mass and strength with all-cause mortality among US older adults.  Med Sci Sports Exerc. 2018;50(3):458-467. doi:10.1249/MSS.0000000000001448PubMedGoogle ScholarCrossref
    32.
    Manolopoulos  KN, Karpe  F, Frayn  KN.  Gluteofemoral body fat as a determinant of metabolic health.  Int J Obes (Lond). 2010;34(6):949-959. doi:10.1038/ijo.2009.286PubMedGoogle ScholarCrossref
    33.
    Caan  BJ, Cespedes Feliciano  EM, Kroenke  CH.  The importance of body composition in explaining the overweight paradox in cancer-counterpoint.  Cancer Res. 2018;78(8):1906-1912. doi:10.1158/0008-5472.CAN-17-3287PubMedGoogle ScholarCrossref
    34.
    Wannamethee  SG, Shaper  AG, Whincup  PH, Lennon  L, Papacosta  O, Sattar  N.  The obesity paradox in men with coronary heart disease and heart failure: the role of muscle mass and leptin.  Int J Cardiol. 2014;171(1):49-55. doi:10.1016/j.ijcard.2013.11.043PubMedGoogle ScholarCrossref
    35.
    Lavie  CJ, McAuley  PA, Church  TS, Milani  RV, Blair  SN.  Obesity and cardiovascular diseases: implications regarding fitness, fatness, and severity in the obesity paradox.  J Am Coll Cardiol. 2014;63(14):1345-1354. doi:10.1016/j.jacc.2014.01.022PubMedGoogle ScholarCrossref
    36.
    Lavie  CJ, Alpert  MA, Arena  R, Mehra  MR, Milani  RV, Ventura  HO.  Impact of obesity and the obesity paradox on prevalence and prognosis in heart failure.  JACC Heart Fail. 2013;1(2):93-102. doi:10.1016/j.jchf.2013.01.006PubMedGoogle ScholarCrossref
    ×