Body Mass Index and Mortality in a Very Large Cohort: Is It Really Healthier to Be Overweight?

Body Mass Index and Mortality in a Very Large Cohort:  Is It Really Healthier to Be Overweight?


Arthur L Klatsky, MD; Jasmine Zhang; Natalia Udaltsova, PhD;
Yan Li, MD, PhD; H Nicole Tran, MD, PhD

Perm J 2017;21:16-142 [Full Citation]
E-pub: 06/29/2017

Body Mass Index and Mortality in a Very Large Cohort:  Is It Really Healthier to Be Overweight?


Context: Controversy persists about optimal body weight. Many experts define “normal” (healthy) body mass index (BMI) as 18.5 to 24.9 kg/m2, 25 to 29.9 kg/m2 as overweight, and 30 kg/m2 or greater as obese. Obesity is subdivided into 30 to 34.9 kg/m2 (Grade 1),
35 to 39.9 kg/m2 (Grade 2), and 40 kg/m2 and above (Grade 3). Studies consistently show higher mortality for underweight and Grade 2 or 3 obesity, but results conflict for the overweight category and Grade 1 obesity.
Objective: To study 30-year risk of death related to baseline BMI.
Design: Retrospective cohort study in a multiracial population of 273,843 persons using logistic regression with 7 covariates (sex, age, race-ethnicity, education, marital status, smoking, alcohol intake).
Main Outcome Measures: Mortality risk by baseline BMI.
Results: With average follow-up exceeding 30 years, there were 103,218 deaths: 41,215 attributed to cardiovascular causes and 62,003 to noncardiovascular causes. Odds ratios (and 95% confidence intervals) for all deaths in BMI categories, with a BMI of 18.5 to 24.9 kg/m2 as the referent, were BMI below 18.5 kg/m2 = 1.1 (1.0-2.0), BMI 25 to 29 kg/m2 = 1.1 (1.1-1.2), BMI 30 to 34 kg/m2 = 1.5 (1.4-1.5), BMI 35 to 39 kg/m2 = 2.1 (1.9-2.3), and BMI 40 kg/m2 or higher = 2.7 (2.4-3.0). Disparities existed regarding age, race/ethnicity, cause of death, and interval to death.
Conclusion: Compared with persons with BMI defined as normal, persons who were underweight, overweight, and obese were at increased risk of death over 30 years.


Despite substantial published literature, there is controversy about the optimal level of body weight and how to best study this important subject.1-5 A relation of weight to health was first noted more than a century ago.6 Interest was stimulated in the 1940s by life insurance company data7 showing increased mortality among persons with body weight 20% or more above “desirable” weights, adjusted for height and body frame. Such persons were charged increased premiums. Desirable weights were defined as the then-current means for each sex at 25 years of age; 20% above these corresponded to a body mass index (BMI) of 27.8 kg/m2 in men and 27.3 kg/m2 in women. These values became the definition of obesity offered by a 1987 National Institutes of Health (NIH) consensus panel. In the late 1990s the World Health Organization (WHO)8 and an NIH panel9 recommended categorization of BMI as follows: 25 to 29.9 kg/m2 as preobesity or overweight, and 30 kg/m2 or greater as obese, with the latter subdivided into 30 to 34.9 kg/m2 (Grade 1 obesity), 35 to  39.9 kg/m2 (Grade 2 obesity) and 40 kg/m2 or greater (Grade 3 obesity). Pleas for standardization of definitions arose.10

The WHO and NIH categories of BMI remain in widespread use and are familiar to clinicians and the public. Early cohort studies of risks associated with higher BMI often used below 25.0 kg/m2 as the referent in categorical models. However, it became clear that overall BMI-related mortality risk is J-shaped, with very lean (underweight) persons also at increased risk.4,5,11,12 The increased risk at low BMIs has been thought possibly related to reverse causality, that is, early illness in some of these persons,13 but this is unproved. An early Kaiser Permanente analysis11 suggested that increased risk of underweight persons might be concentrated in smokers. The J-shaped relationship has led some experts to feel that “normal” (healthy) BMI should be defined as 18.5 to 24.9 kg/m2 and that this should be the standard referent in analytic models.

Studies have consistently shown higher mortality for obese persons, but data are conflicting regarding the overweight category.1-5 A 2013 report4 showed lower mortality for overweight and Grade 1 obese persons, which received widespread attention in the lay press. Some press reports offered a sarcastic view of medical admonitions about the dangers of being overweight or obese.14,15 Some of the disparity between reports may be due to study population differences in age, race, fitness, and sex as well as disparities caused by differences in BMI categorization groups.4

Although BMI clearly is not an ideal measure of actual adiposity,4,5 it has been a widely available and much-used marker. Results with its use correlate well with other markers of obesity, such as waist circumference and waist-to-hip ratio.2 The increased risk for obese persons has been clearest for cardiovascular (CV) diseases,1,4,16-18 but increased risks for other conditions have been reported, including liver disease,19 kidney disease,20 diabetes mellitus,21 and some types of cancer.22-24

Arguably, the obesity epidemic may be leveling off,25 but it remains a major public and individual health concern. Weight control is one of the most frequent issues that health practitioners need to consider when giving medical counsel to patients. Recently reported disparities plus the natural skepticism of many have created confusion among health care practitioners and patients about the optimal level of BMI. Several of our previous studies showed increased risk of mortality from various causes among overweight persons. Therefore, we hypothesized that more detailed study of BMI and total mortality would show this. We believe that the data presented here about mortality risk in a large comprehensive health plan, including stratification by sex and race/ethnicity, will be very helpful to both the public and practitioners.



The institutional review board of the Northern California Kaiser Permanente Medical Care Program approved the study protocols. We performed a retrospective cohort study of 273,843 free-living persons who provided detailed racial classification and underwent health examinations offered by the Kaiser Foundation Heath Plan of Northern California. Voluntarily taken as a health appraisal, the examination included health measurements, such as height and weight, and questionnaire queries about sociodemographic status, habits, and medical history.26 Except for extremes of income, the examinees are thought to represent a cross-section of the population in the area. Detailed racial classification was available for 2 time intervals: 1964 to 1973 and 1978 to 1985. For persons with multiple examinations, baseline data from the first examination in either 1964 to 1973 or 1978 to 1985 were used for all subjects. Mean age at baseline examination was 37.3 years for women and 39.2 years for men.

Mortality Ascertainment

We followed subjects through December 2012 using an automated matching system27 to ascertain death in California that did not require continued Health Plan membership. We accepted primary International Classification of Diseases, Ninth Revision (ICD-9) death certificate codes, converting from International Classification of Diseases, Eighth Revision codes when necessary. Presumption of complete follow-up yielded a calculated 8.21 million person-years of follow-up, but estimates27 suggest a sensitivity of 89% for the method used. We studied total mortality (n = 103,218) in all persons and models stratified by sex, race/ethnicity, age, and smoking. We also studied 3 interval-to-death end points: deaths within 10 years (n = 12,750), deaths at 10 to 19 years (n = 23,873), and deaths after 20 years (n = 66,595). Finally, we studied deaths due to CV causes (ICD-9 codes 390-459, n = 41,215), non-CV causes (all codes except 390-453, n = 62,003), and the largest specific CV and non-CV diagnoses: coronary disease (codes 410-414, n = 20,094), and cancer (codes 140-209, n = 28,013), respectively.

Analytic Methods

We used age-adjusted logistic regression with 7 covariates. They were as follows:

1. sex
2. race/ethnicity: a model comparing blacks, Asians (to indicate Asian Americans), and other races/ethnicities (“others”) with whites as the referent, and another model comparing blacks, Chinese, Japanese, Filipinos, South Asians, other Asians, and other races/ethnicities with whites as the referent
3. education: no college (referent), some college, college graduate
4. marital status: now married (referent), never married, formerly married
5. cigarette smoking: never (referent), ex-smoker, less than 1 pack per day, 1 or more packs per day
6. alcohol drinking: none (referent), fewer than 3 drinks per day, 3 or more drinks per day
7. BMI: for all outcomes, 2 models of BMI categories

a. BMI below 25 kg/m2 was the referent, 25 to 29.9 kg/m2 was overweight, and 30 kg/m2 or higher was obese

b.   BMI 18.5 to 24.9 kg/m2 was the referent, BMI below 18.5 kg/m2 was underweight, 30 to 34.9 kg/m2 was Grade 1 obesity, 35 to 39.9 kg/m2 was Grade 2 obesity, and 40 kg/m2 or greater was Grade 3 obesity.

All covariate data were obtained from computer-stored information collected at the baseline examination. Analyses were performed using SAS statistical software Version 9.3 (SAS Institute, Cary, NC).

In this article, we present results as odds ratios (ORs), 95% confidence intervals (CIs), and associated p values. The term significant is used to refer to estimates with a p value < 0.05. We realize that, with multiple comparisons, many would require a stricter definition. Thus, consistency in multiple strata will also be used as an indicator of validity of associations.



We studied 273,843 subjects, of which 45.1% (rounded) were men and 55.0% were women. The racial composition was 69.0% white, 18.5% black, and 7.6% Asian. The remaining 4.9% were mixed race or other. The largest Asian group was Chinese (3.5% of the total); others were Japanese (1.1%), Filipino, (2.1%), South Asian (0.4%), and other Asian (0.5%).

Distributions of Body Mass Index Categories by Sex and Race

Mean BMI was higher in men (25.2 kg/m2) than in women (23.9 kg/m2), but women were about 10% more likely than men to be obese (BMI ≥ 30 kg/m2), almost entirely because of an excess of obesity in black women (Table 1). Obesity was substantially less prevalent in Asians of both sexes. Among whites and Asians, men were twice as likely as women to be overweight (BMI = 25-29 kg/m2), whereas black men were 50% more likely than black women to be overweight. Women were almost 4 times more likely than men to be underweight (BMI < 18.5 kg/m2). The proportion of underweight persons was greatest in Asians, the only racial group with more underweight than obese persons.

The BMI category distributions for the specific Asian ethnic groups varied slightly (Table 2). Proportions of obese persons ranged from 1.5% of Chinese to 3.2% of Filipinos, and proportions of underweight persons ranged from 5.0% of Filipinos to 8.1% of Chinese. The mean BMIs were also lower among Asians (whites = 24.5 kg/m2, blacks = 25.6 kg/m2, and Asians = 22.6 kg/m2). All Asian ethnic groups had lower mean BMIs than whites or blacks did, ranging from 22.3 kg/m2 in Chinese to 23.3 kg/m2 in Filipinos.

Mortality in All Persons

The J-curve association of BMI to total mortality is evident in Table 3 and Figure 1A. Compared with persons whose BMI ranged from 18.5 to 24.9 kg/m2, underweight men were 32% more likely to die and underweight women were 9% more likely to die. Overweight men were 10% more likely to die and men with Grade 1 obesity were 45% more likely to die. Overweight women were 22% more likely to die, and women with Grade 1 obesity were 56% more likely to die. The footnote data in Table 3 show that the increased risk estimates for the overweight and Grade 1 obese groups were virtually identical in models with referents of less than 25 kg/m2 and 18.5 to 24.9 kg/m2. In both sexes there were progressively larger increases in mortality risk for persons with Grades 2 and 3 obesity. The associations were slightly stronger for men than for women at the extremes of underweight and marked obesity.

Racial-Ethnic Differences in Body Mass Index Mortality Risks

The increased risk of death was similar for overweight and obese whites and blacks (Figure 1B). For example, the ORs (95% CIs) for overweight and Grade 1 obese whites were 1.13 (1.09-1.16) and 1.47 (1.40-1.56), respectively. The corresponding ORs for blacks were 1.14 (1.08-1.21) and 1.46 (1.35-1.58), all with p < 0.001. However, overweight and obese Asians were at substantially higher risk (Figure 1B), with ORs of 1.43 (1.29-1.59) for overweight Asians and 2.51 (1.93-2.56) for Grade 1 obese Asians (both p < 0.001). Underweight Asians had no increased risk (OR = 0.95 [0.78-1.16]); underweight whites had an OR of 1.16 (1.06-1.27, p < 0.01), and underweight blacks had an OR of 1.09 (0.92-1.29).

There was no increased mortality risk among underweight persons in any Asian sex-ethnicity group (Chinese, Japanese, Filipino, South Asian), with nonsignificant ORs slightly below 1.0 for most groups (data not shown). Overweight persons in the specific Asian ethnic groups had the following ORs for total mortality: Chinese = 1.41 (1.21-1.65, p < 0.001), Japanese = 1.37 (1.05-1.80, p = 0.02), Filipinos = 1.71 (1.43-2.05, p < 0.001), South Asian = 1.19 (0.73-1.94, p = 0.5). Obese Asians of each ethnic group had substantially increased mortality risk, but with wide CIs in several subgroups because of small numbers.

Age Differences in Body Mass Index Mortality Risks

The increased mortality risk of overweight and obese persons lessened substantially with increasing baseline age (Figure 1C). For baseline age categories of younger than 40, 40 to 49, 50 to 59, and 60 or more years, the ORs for overweight persons were, respectively, 1.34 (1.29-1.38), 1.22 (1.10-1.28), 1.07 (1.01-1.14), and 1.06 (0.96-1.15). The ORs for Grade 1 obese persons for the 4 age categories were 1.98 (1.86-2.11), 1.54 (1.43-1.67), 1.22 (1.11-1.35), and 1.17 (1.01-1.35).

Body Mass Index Mortality Risk in Smoking Strata

The increased mortality risk of overweight and obese persons was strongest in never smokers (Figure 1D). Increased risk in underweight persons was strongest in ex-smokers (Figure 1D), with OR = 1.31 (1.06-1.67, p = 0.02); this was present in both men (OR 1.66, p = 0.05) and women (OR 1.27, p = 0.07). For overweight persons the increased OR of death was significant in all smoking categories (data not shown).

Interval to Death Models

Data from separate models for 3 follow-up time intervals are presented in Figure 1E. Overweight persons had a slightly decreased risk of dying within 10 years of baseline (OR = 0.95 [0.91-0.99]; p = 0.01), but at 10 to 19 years their risk was slightly increased (OR = 1.05 [1.01-1.08], p = 0.009) and at 20 years or longer their increased risk was more substantial: OR = 1.18 (1.15-1.22, p < 0.001). The Grade 1 obese group had no reduced risk in any timeframe (Figure 1F). Underweight persons had substantially increased risk within 10 years (OR = 1.69 [1.48-1.93], p < 0.001) with some modulation at 10 to 19 years (OR = 1.29 [1.22-1.36], p < 0.001), and no increased risk at more than 20 years (OR = 1.00).

Deaths by Cardiovascular and Noncardiovascular Causes

As shown in Figure 1F for non-CV deaths, the OR for overweight persons was 1.03 (1.01-1.06, p = 0.02) and for CV deaths it was 1.37 (1.33-1.42, p < 0.001). For Grade 1 obese persons, these ORs were 1.23 and 1.99, respectively (both p < 0.0001). The CV/non-CV disparity increased progressively with increasing obesity. For underweight persons, risk was increased for non-CV death (OR 1.18 [1.09-1.27], p < 0.001) but decreased for CV death (OR = 0.84 ([0.74-0.95], p = 0.01). Cancer deaths made up 45.2% of non-CV deaths, and coronary disease comprised 48.8% of CV deaths. For cancer deaths, the ORs for overweight and Grade 1 obese persons were 1.09 (1.05-1.13) and 1.15 (1.08-1.25), respectively (both p < 0.001). For coronary disease deaths, these ORs were 1.43 (1.37-1.50) and 2.16 (1.98-2.28), both with p < 0.001. For underweight persons, the risks for cancer and coronary deaths were 1.12 (1.01-1.23, p = 0.03) and 0.62 (0.51-0.76, p < 0.001), respectively.

Body Mass Index and Mortality in a Very Large Cohort:  Is It Really Healthier to Be Overweight?

Body Mass Index and Mortality in a Very Large Cohort:  Is It Really Healthier to Be Overweight?

Body Mass Index and Mortality in a Very Large Cohort:  Is It Really Healthier to Be Overweight?

Body Mass Index and Mortality in a Very Large Cohort:  Is It Really Healthier to Be Overweight?


Total Mortality in Overweight and Obese Persons

Increased 30-year mortality was shown in overweight or Grade 1 obese persons across multiple strata in our study population; this consistency supports the validity of our findings. Although stratified analyses show disparities in the magnitude of increased risk, none show reduction of total 30-year mortality risk among overweight or Grade 1 obese persons. Only for deaths within 10 years was there a slightly reduced mortality for overweight persons. The greatest increase in risk in overweight and Grade 1 obese subjects was at 20 years or more, but our use of baseline BMI only does not allow us to assess the role of BMI changes in this outcome.

Estimates of increased death risk for overweight or slightly obese persons were quite similar in models that used as the referent less than 25 kg/m2 or 18.5 to 24 kg/m2. Thus, differences in risk estimates related to use of these referents is, in our opinion, an unlikely explanation for disparate findings in published studies. The magnitude of the increased risk among Grade 1 obese persons is substantial (approximately 50%), with even larger increased risk in Grades 2 and 3 obesity (approximately doubled and tripled).

As previously reported,28 increased risk of overweight and obese persons diminished in our data with increasing age. Although probably mostly an artifact of the increasing dominance of age itself and age-related factors, it has been suggested13 that this might be related to selection of healthy, relatively low-risk persons in population study cohorts. This is a possible factor in our study because the subjects voluntarily took the health examination and persons with known chronic illnesses were presumably underrepresented. Another factor could be selective survival of persons resistant to the metabolic consequences of obesity. This touches on the interesting phenomenon known as the “obesity paradox.” This phenomenon refers to data indicating that obese persons with certain medical problems or procedures, including chronic renal failure, myocardial infarction, coronary artery bypass grafting, angioplasty, and heart failure, have a better prognosis than those of normal BMI.29-32 Obesity carries increased risk of certain medical conditions, but in persons with these conditions obesity carries lower risk. Attempts to explain the paradox as a statistical artifact have so far not been conclusive. Unfortunately, our data do not cast light on this matter.

Sex and Race Differences

It is noteworthy that the different distributions of BMI categories between men and women and between blacks and whites did not translate into disparate risks for overweight and Grade 1 obese persons. This contrasts with Asian/white comparisons. Our data also concur with reports33-35 showing that, by the usual categorizations, Asians have lower proportions of overweight and obese persons and that these persons have greater increased death risk than do whites or blacks. Our data also agree with reports33,34 that Asians have a greater proportion of underweight individuals and that underweight Asians have no increased mortality risk. These relationships were generally similar for the various Asian ethnicities. It has been suggested34,36-38 that obesity in Asians be defined as BMI of 25 kg/m2 or greater and overweight as BMI 23 to 24.9 kg/m2. Our data support this concept and the conclusion in a recent review34 that more data are needed in this area. We plan to pursue this area further.

Risk of Underweight Persons

The increased risk of underweight persons was concentrated in men, non-Asian race groups, the first 10 years of follow-up, ex-smokers, and persons dying of non-CV causes. Presumably, the concentration in early years represents to some extent early manifestations of ultimately lethal conditions and supports this previous suggestion.39 These data show the importance of a long follow-up period in the study of BMI and mortality. The greater risk of underweight men compared with underweight women is likely to be an artifact of the smaller proportion of men with BMI under 18.5 kg/m.2 The absence of increased risk among underweight Asians suggests the possible need for revision of both low and high BMI cut-points for this racial group. The high risk of underweight ex-smokers suggests that some ex-smokers are likely to have quit because of symptoms or other evidence of ill health.

Cardiovascular versus Noncardiovascular Causes of Death

As expected,1,4,13,16 the increased risk of death among overweight and obese persons was more substantial among those dying of CV causes. Risk of death for CV causes was actually reduced among underweight persons. Deaths attributed to coronary disease and cancer comprised almost half of the CV and non-CV composites and made proportionate contributions to these associations. Prior reports22-24 indicate substantial variability of obesity-associated risk among cancer types. We plan to pursue further investigation of BMI associations to specific death causes. For now, we point out that demographic disparities in causes of death could help explain disparate findings in various studies.

Covariate Relationships

There was increased death risk associated with increasing age, male sex, black race, smoking, and heavy drinking (Table 4). Higher educational attainment and Asian race were associated with lower risk (Table 4). These expected relationships help to confirm the validity of our analyses.

Limitations and Strengths

Our study had some limitations, including use of only a single baseline BMI measure, which precludes study of effect of both prior and subsequent weight changes, as well as a similar limitation to baseline measurement of covariates. Additionally, the study was limited to deaths in California, and it lacked controls for diet, exercise, and several other relevant traits. These confounder traits, rather than BMI, could be the operative factors responsible for increased mortality. Furthermore, there was a lack of study of intermediary factors between higher BMI and mortality, such as hypertension, blood lipid abnormalities, and, of special importance, diabetes. The absence of more specific data indicative of adiposity (eg, waist-hip ratio, body fat composition) limited our ability to explain sex and race disparities. Finally, it is possible that a health-conscious cohort was selected, which could bias the results.

Strengths include 1) the large size of a free-living and relatively stable study population, 2) exceptionally long follow-up, 3) excellent ascertainment of race/ethnicity, 4) presentation of data about specific Asian ethnic groups, and 5) availability of data enabling control for several important potential confounders, especially smoking.

Public Health Considerations

Because we present no data about changes in BMI, our findings do not directly support recommendations about weight loss to reduce mortality risk in overweight and obese persons. In this regard, the literature is conflicting. Much evidence suggests that weight reduction has a favorable effect on CV risk factors; yet several reports suggest no mortality benefit or even increased mortality in persons who lose weight, even deliberately.40-42 A meta-analysis of randomized controlled trials showed that intentional weight loss in obese adults was associated with a 15% reduction in all-cause mortality.43 These aggregate data do not apply to all persons. As in almost all health issues, advice about losing weight should be individualized.

Body Mass Index and Mortality in a Very Large Cohort:  Is It Really Healthier to Be Overweight?


We conclude that it is not healthier to be overweight. In this analysis in a large multiethnic population, persons with “normal” BMI had the lowest 30-year mortality. These data also support the proposition that there should be lower cutpoints for the definition of overweight and obese in Asians than in whites or blacks.

Disclosure Statement

The author(s) have no conflicts of interest to disclose.


The research was performed at the Kaiser Permanente Northern California Division of Research with support by grants from the Kaiser Foundation Community Budget Program to Yan Li, MD, as principal investigator. Data collection in 1978 to 1985 was supported by a grant to Arthur Klatsky, MD, from the ABMRF/The Foundation for Alcohol Research, Baltimore, MD.

Kathleen Louden, ELS, of Louden Health Communications provided editorial assistance.

How to Cite this Article

Klatsky AL, Zhang J, Udaltsova N, Li Y, Tran HN. Body mass index and mortality in a very large cohort: Is it really healthier to be overweight? Perm J 2017;21:16-142. DOI:

1.    McGee DL; Diverse Populations Collaboration. Body mass index and mortality: A meta-analysis based on person-level data from twenty-six observational studies. Ann Epidemiol 2005 Feb;15(2):87-97. DOI:
    2.    Huxley R, Mendis S, Zheleznyakov E, Reddy S, Chan J. Body mass index, waist circumference and waist:hip ratio as predictors of cardiovascular risk—a review of the literature. Eur J Clin Nutr 2010 Jan;64(1):16-22. DOI:
    3.    Mehta NK, Chang VW. Secular declines in the association between obesity and mortality in
the United States. Popul Dev Rev 2011;37(3):
435-51. DOI:
    4.    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 Jan 2;309(1):71-82. DOI:
    5.    Heymsfield SB, Cefalu WT. Does body mass index adequately convey a patient’s mortality risk? JAMA 2013 Jan 2;309(1):87-8. DOI: Erratum in: JAMA 2013 Feb 6;309(5):442. DOI:
    6.    Symonds B. The influence of overweight and underweight on vitality. 1908. Int J Epidemiol 2010 Aug;39(4):951-7. DOI:
    7.    Lew EA. Mortality statistics for life insurance underwriting. J Am Stat Assoc 1948;43(242):274-89. DOI:
    8.    Obesity: Preventing and managing the global epidemic. Report of a WHO consultation (WHO technical report series 894). Geneva, Switzerland: World Health Organization; 2000.
    9.    Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults—the evidence report. National Institutes of Health. Obes Res 1998 Sep;6 Suppl 2:51S-209S. DOI:
    10.    Kuczmarski RJ, Flegal KM. Criteria for definition of overweight in transition: background and recommendations for the United States. Am J Clin Nutr 2000 Nov;72(5):1074-81.
    11.    Sidney S, Friedman GD, Siegelaub AB. Thinness and mortality. Am J Public Health 1987 Mar;77(3):317-22. DOI:
    12.    Romero-Corral A, Montori VM, Somers VK, et al. Association of bodyweight with total mortality and with cardiovascular events in coronary artery disease: A systematic review of cohort studies. Lancet 2006 Aug 19;368(9536):666-78. DOI:
    13.    Flegal KM, Graubard BI, Williamson DF, Cooper RS. Reverse causation and illness-related weight loss in observational studies of body weight and mortality. Am J Epidemiol 2011 Jan 1;173(1):
1-9. DOI:
    14.    Campos PF. Our absurd fear of fat. The New York Times 2013 Jan 2; Sect A25.
    15.    When heavier is healthier. The Week 2013 Jan 18; p 19.
    16.    Prospective Studies Collaboration; Whitlock G, Lewington S, Sherliker P, et al. Body-mass index and cause-specific mortality in 900 000 adults: Collaborative analyses of 57 prospective studies. Lancet 2009 Mar 28;373(9669):1083-96. DOI:
    17.    Lavie CJ, Milani RV, Ventura HO. Obesity and cardiovascular disease: Risk factor, paradox, and impact of weight loss. J Am Coll Cardiol 2009 May 26;53(21):1925-32. DOI:
    18.    Coutinho T, Goel K, Corrêa de Sá D, et al. Combining body mass index with measures of central obesity in the assessment of mortality in subjects with coronary disease: Role of “normal weight central obesity.” J Am Coll Cardiol 2013 Feb 5;61(5):553-60. DOI:
    19.    Feneberg A, Malfertheiner P. Epidemic trends of obesity with impact on metabolism and digestive diseases. Dig Dis 2012;30(2):143-7. DOI:
    20.    Wickman C, Kramer H. Obesity and kidney disease: Potential mechanisms. Semin Nephrol 2013 Jan;33(1):14-22. DOI:
    21.    Carnethon MR, De Chavez PJ, Biggs ML, et al. Association of weight status with mortality in adults with incident diabetes. JAMA 2012 Aug 8:308(6):581-90. DOI:
    22.    Calle EE. Obesity and cancer. BMJ 2007 Dec 1;335(7630):1107-8. DOI:
    23.    Reeves GK, Pirie K, Beral V, Green J, Spencer E, Bull D; Million Women Study Collaboration. Cancer incidence and mortality in relation to body mass index in the Million Women Study: Cohort study. BMJ 2007 Dec 1;335(7630):1134. DOI:
    24.    Parr CL, Batty GD, Lam TH, et al; Asia-Pacific Cohort Studies Collaboration. Body-mass index and cancer mortality in the Asia-Pacific Cohort Studies Collaboration: Pooled analyses of 424,519 participants. Lancet Oncol 2010 Aug;11(8):741-52. DOI:
    25.    Flegal KM, Carroll MD, Kit BK, Ogden CL. Prevalence of obesity and trends in the distribution of body mass index among US adults, 1999-2010. JAMA 2012 Feb 1;307(5):491-7. DOI:
    26.    Collen MF, Davis LF. The multitest laboratory in health care. J Occup Med 1969 Jul;11(7):355-60.
    27.    Arellano MG, Petersen GR, Petitti DB, Smith RE. The California Automated Mortality Linkage System (CAMLIS). Am J Public Health 1984 Dec;74(12):1324-30. DOI:
    28.    Jahangir E, De Schutter A, Lavie CJ. Low weight and overweightness in older adults: Risk and clinical management. Prog Cardiovasc Dis 2014 Sep-Oct;57(2):127-33. DOI:
    29.    Lainscak M, von Haehling S, Doehner W, Anker SD. The obesity paradox in chronic disease: Facts and numbers. J Cachexia Sarcopenia Muscle 2012 Mar;3(1):1-4. DOI:
    30.    McAuley PA, Blair SN. Obesity paradoxes. J Sports Sci 2011 May;29(8):773-82. DOI:
    31.    Strandberg TE, Strandberg AY, Salomaa VV, et al. Explaining the obesity paradox: Cardiovascular risk, weight change, and mortality during long-term follow-up in men. Eur Heart J 2009 Jul;30(14):1720-7. DOI:
    32.    Dhoot J, Tariq S, Erande A, Amin A, Patel P, Malik S. Effect of morbid obesity on in-hospital mortality and coronary revascularization outcomes after acute myocardial infarction in the United States. Am J Cardiol 2013 Apr 15;111(8):1104-10. DOI:
    33.    Park Y, Wang S, Kitahara CM, et al. Body mass index and risk of death in Asian Americans. Am J Public Health 2014 Mar;104(3):520-5. DOI:
    34.    Nam S. Obesity and Asian Americans in the United States: Systematic literature review. Osong Public Health Res Perspect 2013 Aug;4(4):187-93. DOI:
    35.    Ancheta IB, Carlson JM, Battie CA, Borja-Hart N, Cobb S, Ancheta CV. One size does not fit all: Cardiovascular health disparities as a function of ethnicity in Asian-American women. Appl Nurs Res 2015 May;28(2):99-105. DOI:
    36.    Hsu WC, Araneta MR, Kanaya AM, Chiang JL, Fujimoto W. BMI cut points to identify at-risk Asian Americans for type 2 diabetes screening. Diabetes Care 2015 Jan;38(1):150-8. DOI:
    37.    Staimez LR, Weber MB, Narayan KM, Oza-Frank R. A systematic review of overweight, obesity, and type 2 diabetes among Asian American subgroups. Curr Diabetes Rev 2013 Jul;9(4):312-31. DOI:
    38.    WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 2004 Jan 10;363(9403):157-63. DOI:
    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 Dec 2;363(23):2211-9. DOI:
    40.    Wedick NM, Barrett-Connor E, Knoke JD, Wingard DL. The relationship between weight loss and all-cause mortality in older men and women with and without diabetes mellitus: The Rancho Bernardo study. J Am Geriatr Soc 2002 Nov;50(11):1810-5. DOI:
    41.    Harrington M, Gibson S, Cottrell RC. A review and meta-analysis of the effect of weight loss on all-cause mortality risk. Nutr Res Rev 2009 Jun;22(1):93-108. DOI:
    42.    Higgins M, D’Agostino R, Kannel W, Cobb J, Pinsky J. Benefits and adverse effects of weight loss. Observations from the Framingham Study. Ann Intern Med 1993 Oct 1;119(7 Pt 2):758-63. DOI: Erratum in: Ann Intern Med 1993 Nov 15;119(10):1055. DOI:
    43.    Kritchevsky SB, Beavers KM, Miller ME, et al. Intentional weight loss and all-cause mortality: A meta-analysis of randomized clinical trials. PLOS ONE 2015 Mar 20;10(3):e0121993. DOI:



The Permanente Journal is celebrating it's 20th anniversary year. We look forward to continuing to bring you more high-quality content during the next 20 years.


Sponsored by the National Permanente Medical Groups, The Permanente Press publishes The Permanente Journal and books related to Kaiser Permanente and health care.


25,000 print readers per quarter, 7,628 eTOC readers, and in 2016, 1.4 million page views on TPJ articles in PubMed from a broad international readership.


Articles, editorials, letters to the editor, and other material represent the opinion of the authors. Send your comments to

Copyright 2017 The Permanente Journal - Kaiser Permanente. All Rights Reserved.