 |
|
Associations of General and Abdominal Obesity With Multiple Health Outcomes in Older Women
The Iowa Women's Health Study
Aaron R. Folsom, MD;
Lawrence H. Kushi, ScD;
Kristin E. Anderson, PhD, MPH;
Pamela J. Mink, PhD, MPH;
Janet E. Olson, PhD, MPH;
Ching-Ping Hong, MS;
Thomas A. Sellers, PhD, MPH;
DeAnn Lazovich, PhD;
Ronald J. Prineas, MBBS, PhD
Arch Intern Med. 2000;160:2117-2128.
ABSTRACT
| |
Background Recent clinical guidelines on the health risks of obesity use body mass index (BMI; calculated as weight in kilograms divided by the square of height in meters) and waist circumference, but the waist-hip ratio may provide independent information.
Methods To assess the joint and relative associations of BMI, waist circumference, and waist-hip ratio with multiple disease end points, we conducted a prospective cohort study of 31,702 Iowa women, aged 55 to 69 years and free of cancer, heart disease, and diabetes, assembled by random sampling and mail survey in 1986. Study end points were total and cause-specific mortality and incidence of site-specific cancers and self-reported diabetes, hypertension, and hip fracture over 11 to 12 years.
Results The waist-hip ratio was the best anthropometric predictor of total mortality, with the multivariable-adjusted relative risk for quintile 5 vs 1 of 1.2 (95% confidence interval, 1.1-1.4), compared with 0.91 (95% confidence interval, 0.8-1.0) for BMI and 1.1 (95% confidence interval, 1.0-1.3) for waist circumference. The waist-hip ratio was also associated positively with mortality from coronary heart disease, other cardiovascular diseases, cancer, and other causes. The waist-hip ratio was associated less consistently than BMI or waist circumference with cancer incidence. All anthropometric indexes were associated with incidence of diabetes and hypertension. For example, women simultaneously in the highest quintiles of BMI and waist-hip ratio had a relative risk of diabetes of 29 (95% confidence interval, 18-46) vs women in the lowest combined quintiles.
Conclusion The waist-hip ratio offers additional prognostic information beyond BMI and waist circumference.
INTRODUCTION
EXCESS WEIGHT, often measured as increased body mass index (BMI; calculated as weight in kilograms divided by the square of height in meters) or increased weight for height, has long been considered a risk factor for many chronic diseases. In the past 2 decades, visceral or abdominal obesity, as reflected anthropometrically by an increased waist circumference or waist-hip ratio, has also emerged as an important predictor of risk of obesity-related diseases. However, as discussed in a recent review,1 it is unclear which measure of abdominal obesity best characterizes risk. Recent guidelines addressing obesity2 recommended waist circumference over waist-hip ratio, as waist circumference is simpler to measure and interpret and correlates well with visceral fat measured by computed tomography.1 Yet, waist circumference also is highly correlated with BMI and thus reflects general, and abdominal, obesity.
Most reports associating abdominal obesity with disease have examined men or younger women, have focused on 1 or 2 diseases at a time, or have failed to consider the contribution of abdominal obesity independent of general obesity. Understanding the roles of different patterns of obesity in multiple diseases is important, given the steady increase in body weight during the past 2 decades in the United States.3
The main aim of the Iowa Women's Health Study was to assess the association of body fat distribution and disease incidence in a large cohort of older women. Previously reported findings4-10 from this cohort had limited follow-up. This report extends the follow-up and reports the joint and relative associations of BMI, waist circumference, and waist-hip ratio with multiple disease end points.
SUBJECTS AND METHODS
THE IOWA WOMEN'S HEALTH STUDY
In January 1986, a mailed questionnaire was completed by 41,836 (42.7%) of 98,030 randomly selected women, between the ages of 55 and 69 years, who had a valid Iowa driver's license in 1985. Although driver's license information indicated that respondents were 3 months older than nonrespondents, had a lower BMI by 0.4, and were more likely to live in rural counties of Iowa, the associations of body weight with mortality and cancer incidence were similar in respondents and nonrespondents.11 The baseline questionnaire included standard questions on educational level, smoking status and amount, usual alcohol intake during the past year, hormone replacement therapy status, and reproductive history. Participants were asked 3 questions about whether they participated in any leisure time exercise and, if so, the frequency of moderate- and heavy-intensity activities. These latter 2 questions were combined to create a 3-level activity score (low, medium, and high). A food frequency questionnaire was used to assess dietary intake.12 Prevalent cancers were ascertained by asking the women whether they had ever been told by a physician that they had any form of cancer, excluding skin cancer. Prevalent heart disease was ascertained through self-reports of physician-diagnosed myocardial infarction, angina, or other heart disease. Prevalent hypertension and diabetes were similarly assessed.
Enclosed with the questionnaire were a paper tape measure and written instructions to have a friend measure circumferences of the waist (2.5 cm above the umbilicus) and hips (maximal protrusion). The waist-hip circumference ratio was calculated. Participants reported current height and current weight, from which the BMI was derived. The self-measured or self-reported anthropometric variables obtained by this protocol were valid (intraclass correlation coefficient with measures by trained technician,  0.84) and reliable (intraclass correlation of measures at 2 different periods, 0.85).13
COHORT FOLLOW-UP
Information on the vital status of the cohort was collected by several methods. Participant identifiers (name, address, social security number, birth date, and maiden name) were linked by computer to death certificates at the State Health Registry of Iowa for 1986 through 1996. To identify deaths outside of Iowa and nonfatal, noncancer end points, mailed follow-ups were undertaken in 1987 (91%), 1989 (90%), 1992 (83%), and 1997 (79%) (response rates are given in parentheses); the vital status of nonrespondents was identified by linkage with the National Death Index. We estimate that 99% of deaths in the cohort have been identified. Underlying causes of deaths were coded according to the International Classification of Diseases, Ninth Revision (ICD-9).14 For deaths occurring in Iowa, underlying causes were assigned by the Iowa Department of Health; for deaths outside of Iowa, underlying causes were assigned by an experienced nosologist following International Classification of Diseases, Ninth Revision (ICD-9) rules.
Cancer incidence was identified by computer linkage with the State Health Registry of Iowa, a National Cancer Institute–supported Surveillance, Epidemiology, and End Results cancer registry. Other incident disease end points were obtained during follow-up surveys as the first positive self-report of a physician diagnosis.
DATA ANALYSIS
For this report, we examined mortality from all causes and from 4 mortality subsets: coronary heart disease (CHD), all other cardiovascular disease (CVD), cancer, and all other causes, for which the percentages of deaths were 18%, 13%, 47%, and 22%, respectively. We also examined the incidence of any cancer and common sites in women (breast, lung, colon, uterus, and ovary). Finally, we examined the incidence of self-reported high blood pressure, diabetes, and hip fracture, the latter 2 of which have been shown to be self-reported reasonably accurately in this cohort or elsewhere.6, 15-16 Although self-reports of myocardial infarction and stroke were collected, we chose to present CHD- and CVD-related mortality instead, as potentially more valid end points.
Of the 41,836 women, we first excluded from consideration women who were premenopausal (n = 569); then, women who reported a baseline history of cancer, heart disease, or diabetes (n = 9426); and then, women who had missing data on BMI and waist-hip ratio (n = 139). This left 31,702 for analysis. For incidence analyses of high blood pressure, prevalent cases at baseline were excluded. For uterine and ovarian cancer incidence, women who had undergone a hysterectomy and a bilateral ovariectomy, respectively, were also excluded. For multivariable analyses, we also excluded women who were deemed to have invalid dietary data (n = 2167), namely, 30 or more items missing on the food frequency questionnaire or implausible energy intake (<2520 or 10,584 kJ/d).
Person-years of follow-up for computation of mortality rates were calculated as the time elapsed from completion of the baseline questionnaire to either the end of 1996 or death. For cancer incidence, person-years accumulated from baseline until (1) identified emigration from Iowa (approximately 0.5% annually); (2) identification of a (first) registered cancer diagnosis; (3) death; or (4) December 31, 1996, whichever occurred first. For other, self-reported incident end points, person-years were the sum of the known disease-free period plus half of the period between questionnaires, during which the diagnosis was first made; for women without incident end points, person-time continued until their last completed questionnaire.
Women were categorized according to quintiles (or tertiles when there were few end points) of the baseline anthropometric variables among the total cohort at risk. Age-adjusted relative risks (RRs), their 95% confidence intervals (CIs), and the P value for trend in RRs were calculated by Mantel-Haenszel methods.17 Multivariately adjusted RRs and their 95% CIs were computed by proportional hazards regression using SAS statistical software (program PHREG; SAS Institute Inc, Cary, NC). Covariates were those variables found to be important risk factors in previous Iowa Women's Health Study analyses.6-7,9, 18-19 We computed multivariately adjusted RRs first for BMI, waist-hip ratio, and waist circumference separately. We then included BMI and waist-hip ratio simultaneously in a model to examine their independence. We did not include BMI and waist circumference in the same model because they were highly correlated. However, we did cross classify BMI and waist circumference according to recent obesity guidelines2 and computed age-adjusted odds ratios for pooled end points using unconditional logistic regression. (Person-years were omitted from the tables but are available on request from one of us [A.R.F.].)
RESULTS
DESCRIPTIVE DATA
The cohort included 31,702 postmenopausal women who at baseline were free of cancer, heart disease, and diabetes. The Pearson product moment correlation of BMI with waist circumference was 0.82; BMI with waist-hip ratio, 0.40; and waist circumference with waist-hip ratio, 0.72. Body mass index and waist-hip ratio were associated with most lifestyle variables examined (Table 1). For example, among nondietary factors, BMI and waist-hip ratio were associated negatively with educational level, estrogen use, physical activity, alcohol intake, and multivitamin use. Body mass index, but not waist-hip ratio, was also associated negatively with ever smoking, whereas waist-hip ratio, but not BMI, was associated positively with age.
|
|
|
|
Table 1. Prevalence of Various Baseline Characteristics Within Quintiles of BMI or Waist-Hip Ratio, Iowa Women's Health Study, 1986*
|
|
|
MORTALITY
All Cause
A total of 2476 participants died. In the age-adjusted models, BMI and waist circumference showed U-shaped associations with all-cause mortality (Table 2). After adjustment for other risk factors, women with general obesity were not at increased risk of death: the relative risks for the fifth vs first quintiles were 0.91 (95% CI, 0.8-1.0) for BMI and 1.1 (95% CI, 1.0-1.3) for waist circumference. In contrast, there was a graded risk of mortality across quintiles of waist-hip ratio, with an age-adjusted RR of 1.5 (95% CI, 1.4-1.8) and a risk factor–adjusted relative risk of 1.2 (95% CI, 1.1-1.4) for a comparison of extreme quintiles. When BMI and waist-hip ratio were in the multivariate models together, the RRs were 0.79 (95% CI, 0.7-0.9) comparing extreme quintiles of BMI and 1.4 (95% CI, 1.2-1.6) for waist-hip ratio. Figure 1 shows that there was a positive age-adjusted association of mortality with waist-hip ratio for each stratum of BMI. The highest mortality stratum was that with the lowest BMI and highest waist-hip ratio. Elimination of ever smokers from Figure 1 reduced the 3 highest RRs (in the high waist-hip ratio and low BMI quintiles), but they remained elevated (RRs, 1.2-1.7).
|
|
|
|
Table 2. Association of Anthropometric Variables With Mortality From All Causes, Coronary Heart Disease, Other Cardiovascular Diseases, and Cancer, IWHS, 1986 to 1996*
|
|
|
|
|
|
|
Figure 1. Age-adjusted relative risk of all-cause mortality according to quintiles of body mass index (BMI) and waist-hip ratio, Iowa Women's Health Study, 1986 to 1996. For the cut points of the quintiles, see the third footnote to Table 2.
|
|
|
Coronary Heart Disease
Body mass index, waist-hip ratio, and waist circumference were associated positively with CHD-related mortality (438 deaths), with multivariately adjusted RRs for the fifth vs first quintiles of 1.7, 1.9, and 2.2, respectively (Table 2). When BMI and waist-hip ratio were in the same model, the RRs decreased to 1.3 (95% CI, 0.9-1.9) for BMI and to 1.8 (95% CI, 1.2-2.7) for waist-hip ratio but still suggested that general and abdominal obesity contribute to CHD. A stratified analysis also indicated that a higher BMI and waist-hip ratio were associated with greater CHD-related mortality among the total sample (not shown) and among the never smokers (Figure 2).
|
|
|
|
Figure 2. Age-adjusted relative risk of coronary heart disease–related mortality among never smokers according to tertiles of body mass index (BMI) and waist-hip ratio, Iowa Women's Health Study, 1986 to 1996. The cut points were 24.20 and 28.00 for BMI and 0.791 and 0.863 for waist-hip ratio.
|
|
|
Other CVD
The waist-hip ratio was associated positively, BMI was associated negatively, and waist circumference was not associated with other CVD-related deaths (326 deaths) (Table 2). The RRs for the highest vs lowest quintiles of BMI and waist-hip ratio were 0.60 (95% CI, 0.4-0.9) and 1.7 (95% CI, 1.1-2.7), after adjustment for covariates and each other.
Cancer
The number of participants who died of cancer was 1156. Body mass index, waist-hip ratio, and waist circumference were not significantly associated with cancer-related mortality after adjustment for other risk factors (Table 2).
Other Causes
Body mass index was associated negatively, waist-hip ratio was associated positively, and waist circumference was not associated with the residual group of deaths (556 deaths) (data not shown). The RRs for the highest vs the lowest quintiles of BMI and waist-hip ratio were 0.51 (95% CI, 0.4-0.7) and 1.5 (95% CI, 1.1-2.0), respectively, after adjustment for covariates and each other.
CANCER INCIDENCE
Any Cancer
Cancer incidence (3738 events) tended to be associated positively with all 3 anthropometric variables, with RRs between 1.1 and 1.4 for the highest vs the lowest quintiles (Table 3).
|
|
|
|
Table 3. Association of Anthropometric Variables With Incidence of Various Cancers, IWHS, 1986 to 1996*
|
|
|
Breast Cancer
Body mass index and waist circumference were moderately strongly associated with breast cancer incidence (n = 1299), with risk factor–adjusted RRs for extreme quintiles being 1.6 and 1.7, respectively (Table 3). The RR for waist-hip ratio was smaller (RR, 1.3) and attenuated further when BMI was in the model (RR, 1.1). However, those in the lowest combined quintiles of BMI and waist-hip ratio were at the lowest risk of breast cancer (Figure 3).
|
|
|
|
Figure 3. Age-adjusted relative risk of incident breast cancer according to quintiles of body mass index (BMI) and waist-hip ratio, Iowa Women's Health Study, 1986 to 1996. For the cut points of the quintiles, see the third footnote to Table 2.
|
|
|
Colon Cancer
The associations of anthropometric variables with colon cancer (n = 462) (Table 3) mirrored those for breast cancer.
Lung Cancer
Body mass index was associated negatively with lung cancer incidence (n = 386), even after multivariate adjustment (Table 3). In contrast, the waist-hip ratio and waist circumference were not associated independently with lung cancer incidence. Elimination of ever smokers left only 52 persons with incident lung cancers, among whom the age-adjusted RRs across quartiles of BMI were 1.00, 0.58, 0.62, 0.34, and 0.56 (P = .09 for trend). There was no age-adjusted association of waist-hip ratio and waist circumference with lung cancer among never smokers.
Uterine Cancer
Body mass index and waist circumference were strong predictors of uterine cancer incidence (n = 298), with approximately 4-fold higher incidence for the fifth vs the first quintile but little association across the middle quintiles (Table 3). The association of waist-hip ratio with uterine cancer incidence was eliminated with adjustment for, or stratification by, BMI (Table 3 and Figure 4).
|
|
|
|
Figure 4. Age-adjusted relative risk of incident uterine cancer according to tertiles of body mass index (BMI) and waist-hip ratio, Iowa Women's Health Study, 1986 to 1996. The cut points were 24.20 and 28.00 for BMI and 0.791 and 0.863 for waist-hip ratio.
|
|
|
Ovarian Cancer
Body mass index was not associated, and waist circumference and waist-hip ratio were positively but not monotonically associated, with ovarian cancer incidence (n = 141) (Table 3). The risk factor–adjusted RR comparing extreme quintiles of waist-hip ratio was 2.0 (95% CI, 1.1-3.7), and this value was not changed after adding BMI to the model.
INCIDENCE OF OTHER DISEASES
Diabetes
Body mass index, waist-hip ratio, and waist circumference were strong risk factors for incidence of self-reported diabetes (n = 1578) (Table 4). Among the 3 anthropometric variables, waist circumference displayed the greatest RRs. As shown in Figure 5, BMI and waist-hip ratio appeared to contribute independently to diabetes incidence; the age-adjusted RR of diabetes for the highest combined quintiles vs the lowest was exceptionally high, 29 (95% CI, 18-46).
|
|
|
|
Table 4. Association of Anthropometric Variables With Incidence of Self-Reported Diabetes, High Blood Pressure, and Hip Fracture, IWHS, 1986 to 1996*
|
|
|
|
|
|
|
Figure 5. Age-adjusted relative risk of incident diabetes according to quintiles of body mass index (BMI) and waist-hip ratio, Iowa Women's Health Study, 1986 to 1996. For the cut points of the quintiles, see the third footnote to Table 2.
|
|
|
High Blood Pressure
All 3 anthropometric variables were associated positively with incidence of self-reported high blood pressure (n = 4077). Relative risks were approximately 2.0 for highest vs lowest quintiles of each variable (Table 4), suggesting that both general and abdominal obesity are risk factors. The age-adjusted RR for highest vs lowest combined quintiles of BMI and waist-hip ratio (Figure 6) was 2.8 (95% CI, 2.4-3.3).
|
|
|
|
Figure 6. Age-adjusted relative risk of incident hypertension according to quintiles of body mass index (BMI) and waist-hip ratio, Iowa Women's Health Study, 1986 to 1996. For the cut points of the quintiles, see the third footnote to Table 2.
|
|
|
Hip Fracture
Body mass index was associated inversely with occurrence of self-reported hip fracture (n = 484), whereas waist-hip ratio was associated slightly positively and waist circumference was not at all associated with hip fracture (Table 4). In the multivariate model including both anthropometric variables, the RRs comparing extreme quintiles were 0.49 (95% CI, 0.4-0.7) for BMI and 1.6 (95% CI, 1.1-2.2) for waist-hip ratio. Figure 7 depicts the contrasting age-adjusted joint associations of BMI and waist-hip ratio with hip fracture.
|
|
|
|
Figure 7. Age-adjusted relative risk of hip fracture according to quintiles of body mass index (BMI) and waist-hip ratio, Iowa Women's Health Study, 1986 to 1996. For the cut points of the quintiles, see the third footnote to Table 2.
|
|
|
POOLED END POINT
Recently, an expert panel proposed joint BMI (6 classes from underweight [BMI, <18.5] to obesity class 3 [BMI, 40]) and waist circumference ( 88 or >88 cm) cut points to stratify patients for risk of diabetes, hypertension, and CVD.2 The left half of Table 5 summarizes the expert consensus panel's categories of risk for the different body size groupings, and the right half shows estimated risk based on Iowa Women's Health Study data. For this analysis, we excluded participants with hypertension at baseline and used 2 pooled end points, namely, (1) occurrence of incident diabetes, incident hypertension, or any CVD-related death (including CHD); or (2) occurrence of incident diabetes, hypertension, hip fracture, or cancer or all-cause death. Because waist circumference and BMI were highly correlated, there were few women in either the high BMI and low waist circumference category or the low BMI and high waist circumference category (Table 5). The age-adjusted odds ratios from our cohort for the composite end point of diabetes, hypertension, or death from CVD seemed to correspond to the consensus risk categories. However, BMI was not predictive of the broader end point (also including cancer incidence, hip fracture incidence, and all deaths) in women with waist circumferences of 88 cm or less. Adjustment of the data for other covariates, including smoking, did not materially alter these odds ratio estimates.
|
|
|
|
Table 5. Age-Adjusted OR of Any Designated End Point During Follow-up in Relation to Categories of BMI and Waist Circumference for the IWHS Compared With the Obesity Panel Consensus Risk Category*
|
|
|
COMMENT
Our main aim was to examine the joint risk and RR of general obesity vs abdominal obesity on multiple health outcomes in a cohort of older women initially free of cancer, heart disease, and diabetes and followed up for 11 to 12 years. Our hypothesis was that the relative contributions of BMI (primarily a marker of general obesity), waist-hip ratio (primarily a marker of abdominal obesity), and waist circumference (a marker of general and abdominal obesity) would vary among diseases. Understanding the various patterns of obesity that lead to different diseases may offer clues to their etiologies and help guide clinical decision making.
MORTALITY
General obesity appeared to be a poor predictor of total mortality in these older women, but abdominal obesity, as measured by waist-hip ratio, showed a positive, monotonic, and independent association with total mortality. As reported after 5 years of follow-up,9 the women with the highest risk of death in this cohort were those with a low BMI and a high waist-hip ratio (Figure 1). This was also true, although attenuated, among the never smokers. Thus, a high waist-hip ratio appears to be the best anthropometric predictor of death in this cohort. Our results, nevertheless, should not be interpreted to mean that a high BMI is not a potential health hazard, especially when BMI becomes elevated early in life20; a low BMI in some older adults may reflect ill health that we could not control for by excluding prevalent cancer, heart disease, and diabetes.
Abdominal fat measures (waist-hip ratio or waist circumference) appeared to show a monotonic association with CHD-related deaths, but only the highest quintile of BMI carried an increased risk of CHD-related mortality. This is generally consistent with previous prospective findings,21-25 suggesting that abdominal obesity, in addition to a high BMI, is an important risk factor for CHD-related mortality or incidence. Abdominal obesity appears to be a particularly good indicator of the adverse metabolic risk factor profile (ie, hyperinsulinemia, dyslipidemia, hypertension, and impaired fibrinolytic capacity),26-27 which increases the risk of CHD. In contrast with CHD, other cardiovascular-related deaths were positively associated with waist-hip ratio and negatively associated with BMI, when adjusted for each other. Cancer-related mortality was only weakly associated with measures of obesity.
The finding that "other causes" of death showed a positive association with waist-hip ratio but a negative association with measures of general obesity is difficult to interpret. The component causes of the other deaths were a heterogeneous mix, including injury and poisoning, chronic pulmonary disease, and acute conditions that developed during follow-up. There were too few events to analyze every cause of death separately. However, risk of death from injury or poisoning, deaths that cannot easily be attributed to biological effects of obesity, appears to be elevated, albeit nonsignificantly, among women with greater body size. This may reflect residual effects of lower socioeconomic status on injury- and poisoning-associated mortality, although we did adjust for educational level. Future research should address whether general or abdominal obesity contributes to other preventable diseases or, conversely, whether the underlying diseases alter body composition.
INCIDENCE
The incidence of self-reported diabetes was strongly associated with all of the measures of obesity. Women in the highest quintiles of BMI and waist-hip ratio had a dramatic RR of 29 compared with women in the lowest combined quintiles. These findings are consistent with those of previous prospective studies,28-32 and emphasize the role of general and abdominal obesity in causing insulin resistance26, 33 and, ultimately, diabetes. However, even women in the lowest quintile of BMI had a markedly elevated diabetes risk if they also had a high waist-hip ratio (Figure 5), suggesting the potentially pivotal role of visceral adipose tissue in insulin resistance.26 Weight loss improves insulin sensitivity,34 and efforts are under way to determine whether weight control and other lifestyle modifications can prevent the onset of diabetes.35
The incidence of reported hypertension was slightly more strongly associated with general obesity than abdominal obesity, although those at highest risk (RR, approximately 3.0) of hypertension were in the highest quintiles of BMI and waist-hip ratio. Previous studies33, 36 have also suggested a somewhat stronger association of high blood pressure with generalized obesity than with abdominal obesity, with insulin resistance as the potential mechanism most commonly evoked.37
Women with a higher BMI reported a decreased occurrence of hip fracture than did women with a lower BMI, similar to other prospective studies38 and in line with increased estrogen levels in obese women.39-40 In contrast, hip fracture incidence was not related to waist circumference, and hip fracture incidence increased with higher waist-hip ratio adjusted for BMI. Possible explanations are that women with a high waist-hip ratio are more prone to falling, have more osteoporosis, or have less fat padding to protect against hip fracture on falling. Unfortunately, we have no data in this cohort on bone density or rates of falling.
Overall, the incidence of any cancer was positively, albeit weakly, associated with both general and abdominal obesity. Previous prospective studies have reported that general obesity increases the incidence of postmenopausal breast cancer,41-42 colon cancer,43-44 and uterine cancer,45-46 but few have examined abdominal obesity. In our study, general obesity appeared to be more strongly associated with breast cancer, colon cancer, and uterine cancer than did abdominal obesity. Increased adipose conversion of androgens to estrogens47 is usually cited as a mechanism for obesity increasing the risk of these estrogen-dependent cancers. Abdominal fat distribution does not appear to further increase total estrogen concentrations in obese postmenopausal women, but increases androgen levels and lowers sex hormone–binding globulin levels.39 This may explain why abdominal obesity is not associated, beyond general obesity, with breast, colon, and uterine cancer.
Others48-49 have reported little association of ovarian cancer with general obesity. In contrast, as reported10 after 7 years of follow-up, ovarian cancer was associated positively with abdominal obesity in this cohort. Because a high waist-hip ratio is associated with hyperinsulinemia,33 hyperandrogenemia,39 and polycystic ovaries,50 1 or more of these 3 factors may increase ovarian cancer risk.
Associations of anthropometric variables with lung cancer may be confounded by smoking, despite statistical adjustment. Analysis for never smokers suggested that, although not quite statistically significant, women with a low BMI independently could be at increased risk of lung cancer. Reasons for such an association, if real, are unclear.
COMBINED END POINT IN RELATION TO OBESITY GUIDELINES
Cross classifying BMI by waist-hip ratio permitted sufficient numbers of events to differentiate patterns of obesity with disease occurrence. Yet, recent guidelines for the identification, evaluation, and treatment of obesity2 incorporate BMI and waist circumference in the assessment, not waist-hip ratio. Because BMI and waist circumference are highly correlated, some of the recommended categories for risk stratification—namely, high BMI and low waist circumference or low BMI and high waist circumference—have too few women to be useful. Nevertheless, our data do corroborate that use of BMI and waist circumference may better differentiate risk of diabetes, hypertension, and CVD than BMI alone. However, BMI was not valuable in predicting risk of the pooled end point, including cancer, hip fracture, and all deaths, when waist circumference was 88 cm or less (Table 5).
LIMITATIONS
The potential drawbacks of this study warrant consideration. The covariates and some nonfatal end points were self-reported, but we chose nonfatal end points that are self-reported fairly accurately.15-16,51 We did not have data on blood pressure, lipid levels, or other potentially valuable physiologic measures. Misclassification of these self-reported variables may have led to bias, although it is difficult to imagine that bias would account for different patterns of associations for different anthropometric indexes. Anthropometric indexes were self-measured, but we have documented their validity.13 It is possible that relations between body size and disease differ according to the duration of obesity or the age of the study population. Furthermore, even though we excluded women with known heart disease, cancer, and diabetes at baseline, other or subclinical diseases could have caused some of these older women to have lost weight before baseline. However, it was previously shown that excluding women with weight loss since the age of 50 years did not alter mortality results appreciably.9 Finally, these results apply to older white women and may not generalize to other ethnic groups, to younger women, or to men.
CONCLUSIONS
Clinical guidelines using BMI and waist circumference2 indeed identify older women at risk of diabetes, hypertension, and CVD. The high correlation between BMI and waist circumference, however, leads to categories that actually contain few women. Waist-hip circumference further identifies women at increased risk of death and several other important illnesses; it could be considered for additional risk stratification.
AUTHOR INFORMATION
Accepted for publication December 16, 1999.
This study was supported by grant R01 CA39742 and training grant T32 CA09607 (Dr Mink) from the National Cancer Institute, Bethesda, Md.
We thank Laura Kemmis for manuscript preparation.
Reprints: Aaron R. Folsom, MD, Division of Epidemiology, School of Public Health, University of Minnesota, 1300 S Second St, Suite 300, Minneapolis, MN 55454-1015 (e-mail: folsom{at}epi.umn.edu).
From the Division of Epidemiology, School of Public Health, University of Minnesota, Minneapolis (Drs Folsom, Kushi, Anderson, Mink, Lazovich, and Prineas and Ms Hong); and the Mayo Foundation, Rochester, Minn (Drs Olson and Sellers).
REFERENCES
| |
1. Molarius A, Seidell JC. Selection of anthropometric indicators for classification of abdominal fatness: a critical review. Int J Obes Relat Metab Disord. 1998;22:719-727.
FULL TEXT
|
ISI
| PUBMED
2. Expert Panel on the Identification, Evaluation, and Treatment of Overweight and Obesity in Adults. Executive summary of the clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults. Arch Intern Med. 1998;158:1855-1867.
FREE FULL TEXT
3. Kuczmarski RJ, Flegal KM, Campbell SM, Johnson CL. Increasing prevalence of overweight among US adults: the National Health and Nutrition Examination Surveys, 1960-1991. JAMA. 1994;272:205-211.
FREE FULL TEXT
4. Folsom AR, Kaye SA, Potter JD, Prineas RJ. Association of incident carcinoma of the endometrium with body weight and fat distribution in older women: early findings of the Iowa Women's Health Study. Cancer Res. 1989;49:6828-6831.
FREE FULL TEXT
5. Folsom A, Prineas R, Kaye S, Munger R. Incidence of hypertension and stroke in relation to body fat distribution and other risk factors in older women. Stroke. 1990;21:701-706.
FREE FULL TEXT
6. Kaye SA, Folsom AR, Sprafka JM, Prineas RJ, Wallace RB. Increased incidence of diabetes mellitus in relation to abdominal adiposity in older women. J Clin Epidemiol. 1991;44:329-334.
FULL TEXT
|
ISI
| PUBMED
7. Sellers TA, Kushi LH, Potter JD, et al. Effect of family history, body fat distribution, and reproductive factors on risk of postmenopausal breast cancer. N Engl J Med. 1992;326:1323-1329.
ABSTRACT
8. Prineas R, Folsom A, Kaye SA. Central adiposity and increased risk of coronary artery disease mortality in older women. Ann Epidemiol. 1993;3:35-41.
PUBMED
9. Folsom AR, Kaye SA, Sellers TA, et al. Body fat distribution and 5-year risk of death in older women. JAMA. 1993;269:483-487.
FREE FULL TEXT
10. Mink PJ, Folsom AR, Sellers TA, Kushi LH. Physical activity, waist-to-hip ratio, and other risk factors for ovarian cancer: a follow-up study of older women. Epidemiology. 1996;7:38-45.
ISI
| PUBMED
11. Bisgard KM, Folsom AR, Hong CP, Sellers TA. Mortality and cancer rates in nonrespondents to a prospective study of older women: 5-year follow-up. Am J Epidemiol. 1994;139:990-1000.
FREE FULL TEXT
12. Rimm E, Giovannucci E, Stampfer M, Colditz G, Litin L, Willett W. Reproducibility and validity of an expanded self-administered semiquantitative food frequency questionnaire among male health professionals. Am J Epidemiol. 1992;135:1114-1126.
FREE FULL TEXT
13. Kushi LH, Kaye SA, Folsom AR, Soler JT, Prineas RJ. Accuracy and reliability of self-measurement of body girths. Am J Epidemiol. 1988;128:740-748.
FREE FULL TEXT
14. World Health Organization. International Classification of Diseases, Ninth Revision (ICD-9). Geneva, Switzerland: World Health Organization; 1977.
15. Munger RG, Cerhan JR, Chiu BC. Prospective study of dietary protein intake and risk of hip fracture in postmenopausal women. Am J Clin Nutr. 1999;69:147-152.
FREE FULL TEXT
16. Midthjell K, Holmen J, Bjørndal A, et al. Is questionnaire information valid in the study of a chronic disease such as diabetes? the Nord-Trøndelag Diabetes Study. J Epidemiol Community Health. 1992;46:537-542.
FREE FULL TEXT
17. Mantel N. Chi-square tests with one degree of freedom: extensions of the Mantel-Haenszel procedures. J Am Stat Assoc. 1963;58:690-700.
FULL TEXT
|
ISI
18. Kushi LH, Folsom AR, Prineas RJ, Mink PJ, Wu Y, Bostick RM. Dietary antioxidant vitamins and death from coronary heart disease in postmenopausal women. N Engl J Med. 1996;334:1156-1162.
FREE FULL TEXT
19. Jacobs DR Jr, Meyer KA, Kushi LH, Folsom AR. Is whole grain intake associated with reduced total and cause-specific death rates in older women? the Iowa Women's Health Study. Am J Public Health. 1999;89:322-329.
FREE FULL TEXT
20. Willett WC, Manson JE, Stampfer MJ, et al. Weight, weight change, and coronary heart disease in women: risk within the "normal" weight range. JAMA. 1995;273:461-465.
FREE FULL TEXT
21. Larsson B, Svardsudd K, Welin L, Wilhelmsen L, Bjorntorp P, Tibblin G. Abdominal adipose tissue distribution, obesity, and risk of cardiovascular disease and death: 13 year follow up of participants in the study of men born in 1913. Br Med J (Clin Red Ed). 1984;288:1401-1404.
22. Lapidus L, Bengtsson C, Larsson B, et al. Distribution of adipose tissue and risk of cardiovascular disease and death. Br Med J (Clin Red Ed). 1984;289:1257-1261.
23. Stevens J, Keil JE, Rust PF, Tyroler HA, Davis CE, Gazes PC. Body mass index and body girths as predictors of mortality in black and white women. Arch Intern Med. 1992;152:1257-1262.
FREE FULL TEXT
24. Rimm EB, Stampfer MJ, Giovannucci E, et al. Body size and fat distribution as predictors of coronary heart disease among middle-aged and older US men. Am J Epidemiol. 1995;141:1117-1127.
FREE FULL TEXT
25. Rexrode KM, Carey VJ, Hennekens CH, et al. Abdominal adiposity and coronary heart disease in women. JAMA. 1998;280:1843-1848.
FREE FULL TEXT
26. Bujalska IJ, Kumar S, Stewart PM. Does central obesity reflect "Cushing's disease of the omentum"? Lancet. 1997;349:1210-1213.
FULL TEXT
|
ISI
| PUBMED
27. Alessi MC, Peiretti F, Morange P, Henry M, Nalbone G, Juhan-Vague I. Production of plasminogen activator inhibitor 1 by human adipose tissue: possible link between visceral fat accumulation and vascular disease. Diabetes. 1997;46:860-867.
ABSTRACT
28. Ohlson LO, Larsson B, Svardsudd K, et al. The influence of body fat distribution on the incidence of diabetes mellitus: 13.5 years of follow-up of the participants in the study of men born in 1913. Diabetes. 1985;34:1055-1058.
ABSTRACT
29. Lundgren H, Bengtsson C, Blohme G, Lapidus L, Sjostrom L. Adiposity and adipose tissue distribution in relation to incidence of diabetes in women: results from a prospective population study in Gothenburg, Sweden. Int J Obes. 1989;13:413-423.
ISI
| PUBMED
30. Feskens EJ, Kromhout D. Cardiovascular risk factors and the 25-year incidence of diabetes mellitus in middle-aged men: the Zutphen Study. Am J Epidemiol. 1989;130:1101-1108.
FREE FULL TEXT
31. Carey V, Walters E, Colditz G, et al. Body fat distribution and risk of non–insulin-dependent diabetes in women. Am J Epidemiol. 1997;145:614-619.
FREE FULL TEXT
32. Chan JM, Rimm EB, Colditz GA, et al. Obesity, fat distribution and weight gain as risk factors for clinical diabetes in men. Diabetes Care. 1994;17:961-969.
ABSTRACT
33. Folsom AR, Burke GL, Ballew C, et al. Relation of body fatness and its distribution to cardiovascular risk factors in young blacks and whites: the role of insulin. Am J Epidemiol. 1989;130:911-924.
FREE FULL TEXT
34. Colman E, Katzel LI, Rogus E, Coon P, Muller D, Goldberg AP. Weight loss reduces abdominal fat and improves insulin action in middle-aged and older men with impaired glucose tolerance. Metabolism. 1995;44:1502-1508.
FULL TEXT
|
ISI
| PUBMED
35. The Diabetes Prevention Program Research Group. The Diabetes Prevention Program: design and methods for a clinical trial in the prevention of type 2 diabetes. Diabetes Care. 1999;22:623-634.
ABSTRACT
36. Hartz AJ, Rupley DC, Rimm AA. The association of girth measurements with disease in 32,856 women. Am J Epidemiol. 1984;119:71-80.
FREE FULL TEXT
37. Haffner SM. Obesity, body fat distribution, and insulin resistance: clinical relevance. In: Izzo JL Jr, Black HR, eds. Hypertension Primer. Dallas, Tex: American Heart Association; 1993:158-160.
38. Cummings SR, Kelsey JL, Nevitt MC, O'Dowd KJ. Epidemiology of osteoporosis and osteoporotic fractures. Epidemiol Rev. 1985;7:178-208.
FREE FULL TEXT
39. Kaye SA, Folsom AR, Soler JT, Prineas RJ, Potter JD. Associations of body mass and fat distribution with sex hormone concentrations in post-menopausal women. Int J Epidemiol. 1991;20:151-156.
FREE FULL TEXT
40. Cauley JA, Gutal JP, Kuller LH, LeDonne D, Powell JG. The epidemiology of serum sex hormones in postmenopausal women. Am J Epidemiol. 1989;129:1120-1131.
FREE FULL TEXT
41. Huang Z, Hankinson SE, Colditz GA, et al. Dual effects of weight and weight gain on breast cancer risk. JAMA. 1997;278:1407-1411.
FREE FULL TEXT
42. Hunter DJ, Willett WC. Diet, body size, and breast cancer. Epidemiol Rev. 1993;15:110-132.
FREE FULL TEXT
43. Martinez ME, Giovannucci E, Spiegelman D, Hunter DJ, Willett WC, Colditz GA. Leisure-time physical activity, body size, and colon cancer in women. J Natl Cancer Inst. 1997;89:948-955.
FREE FULL TEXT
44. Le Marchand L, Wilkens LR, Mi MP. Obesity in youth and middle age and risk of colorectal cancer in men. Cancer Causes Control. 1992;3:349-354.
FULL TEXT
|
ISI
| PUBMED
45. Le Marchand L, Wilkens LR, Mi MP. Early-age body size, adult weight gain and endometrial cancer risk. Int J Cancer. 1991;48:807-811.
ISI
| PUBMED
46. Tretli S, Magnus K. Height and weight in relation to uterine corpus cancer morbidity and mortality: a follow-up study of 570,000 women in Norway. Int J Cancer. 1990;46:165-172.
ISI
| PUBMED
47. Siiteri PK. Adipose tissue as a source of hormones. Am J Clin Nutr. 1987;45:277-282.
FREE FULL TEXT
48. Farrow DC, Weiss NS, Lyon JL, Daling JR. Association of obesity and ovarian cancer in a case-control study. Am J Epidemiol. 1989;129:1300-1304.
FREE FULL TEXT
49. Shu XO, Gao YT, Yuan JM, Ziegler RG, Brinton LA. Dietary factors and epithelial ovarian cancer. Br J Cancer. 1989;59:92-96.
ISI
| PUBMED
50. Bates GW, Whitworth NS. Effect of body weight reduction on plasma androgens in obese infertile women. Fertil Steril. 1982;38:406-409.
ISI
| PUBMED
51. Mackenbach JP, Looman CWN, van der Meer JBW. Differences in the misreporting of chronic conditions, by level of education: the effects of inequalities in prevalence rates. Am J Public Health. 1996;86:706-711.
FREE FULL TEXT
 CiteULike  Connotea  Del.icio.us  Digg  Reddit  Technorati
What's this?
RELATED ARTICLE
Archives of Internal Medicine Reader's Choice: Continuing Medical Education
Arch Intern Med. 2000;160(14):2228.
FULL TEXT
THIS ARTICLE HAS BEEN CITED BY OTHER ARTICLES
|
A Longitudinal Study of the Metabolic Syndrome and Risk of Postmenopausal Breast Cancer
Kabat et al.
Cancer Epidemiol. Biomarkers Prev. 2009;18:2046-2053.
ABSTRACT
| FULL TEXT
Mortality, Health Outcomes, and Body Mass Index in the Overweight Range: A Science Advisory From the American Heart Association
Lewis et al.
Circulation 2009;119:3263-3271.
FULL TEXT
Estimates of excess deaths associated with body mass index and other anthropometric variables
Flegal and Graubard
Am. J. Clin. Nutr. 2009;89:1213-1219.
ABSTRACT
| FULL TEXT
Relationship of adiposity with arterial stiffness as mediated by adiponectin in older men and women: the Hoorn Study
Snijder et al.
Eur J Endocrinol 2009;160:387-395.
ABSTRACT
| FULL TEXT
Association of Multiple Anthropometrics of Overweight and Obesity With Incident Heart Failure: The Atherosclerosis Risk in Communities Study
Loehr et al.
Circ Heart Fail 2009;2:18-24.
ABSTRACT
| FULL TEXT
Surgery for obesity in older women
Miller and Kral
Menopause Int 2008;14:155-162.
ABSTRACT
| FULL TEXT
Reducing overweight and obesity: closing the gap between primary care and public health
Anderson
Fam Pract 2008;25:i10-i16.
ABSTRACT
| FULL TEXT
General and Abdominal Adiposity and Risk of Death in Europe
Pischon et al.
NEJM 2008;359:2105-2120.
ABSTRACT
| FULL TEXT
Measures of Obesity and Cardiovascular Risk Among Men and Women
Gelber et al.
J Am Coll Cardiol 2008;52:605-615.
ABSTRACT
| FULL TEXT
Which Measures of Obesity Best Predict Cardiovascular Risk?
Litwin
J Am Coll Cardiol 2008;52:616-619.
FULL TEXT
Waist Circumference and Mortality
Koster et al.
Am J Epidemiol 2008;167:1465-1475.
ABSTRACT
| FULL TEXT
Impact of Functional Limitations and Medical Comorbidity on Subsequent Weight Changes and Increased Depressive Symptoms in Older Adults
Forman-Hoffman et al.
J Aging Health 2008;20:367-384.
ABSTRACT
Abdominal Adiposity and Diabetes Risk: The Importance of Precise Measures and Longitudinal Studies
Hanley and Wagenknecht
Diabetes 2008;57:1153-1155.
FULL TEXT
Abdominal Obesity and the Risk of All-Cause, Cardiovascular, and Cancer Mortality: Sixteen Years of Follow-Up in US Women
Zhang et al.
Circulation 2008;117:1658-1667.
ABSTRACT
| FULL TEXT
Cardiovascular Risk Factors, Mortality, and Overweight
McTigue and Kuller
JAMA 2008;299:1260-1261.
FULL TEXT
Body Mass and Endometrial Cancer Risk by Hormone Replacement Therapy and Cancer Subtype
McCullough et al.
Cancer Epidemiol. Biomarkers Prev. 2008;17:73-79.
ABSTRACT
| FULL TEXT
Body Fat Distribution and Risk of Coronary Heart Disease in Men and Women in the European Prospective Investigation Into Cancer and Nutrition in Norfolk Cohort: A Population-Based Prospective Study
Canoy et al.
Circulation 2007;116:2933-2943.
ABSTRACT
| FULL TEXT
Cardiorespiratory Fitness and Adiposity as Mortality Predictors in Older Adults
Sui et al.
JAMA 2007;298:2507-2516.
ABSTRACT
| FULL TEXT
European guidelines on cardiovascular disease prevention in clinical practice: executive summary: Fourth Joint Task Force of the European Society of Cardiology and Other Societies on Cardiovascular Disease Prevention in Clinical Practice (Constituted by representatives of nine societies and by invited experts)
Authors/Task Force Members et al.
Eur Heart J 2007;28:2375-2414.
FULL TEXT
Diabetes, metabolic syndrome, and breast cancer: a review of the current evidence
Xue and Michels
Am. J. Clin. Nutr. 2007;86:823S-835S.
ABSTRACT
| FULL TEXT
A Prospective Cohort of American Indian and Alaska Native People: Study Design, Methods, and Implementation
Slattery et al.
Am J Epidemiol 2007;166:606-615.
ABSTRACT
| FULL TEXT
Can EGCG Reduce Abdominal Fat in Obese Subjects?
Hill et al.
J. Am. Coll. Nutr. 2007;26:396S-402S.
ABSTRACT
| FULL TEXT
Relation of body mass index and waist-to-height ratio to cardiovascular disease risk factors in children and adolescents: the Bogalusa Heart Study
Freedman et al.
Am. J. Clin. Nutr. 2007;86:33-40.
ABSTRACT
| FULL TEXT
Whole-grain consumption is associated with a reduced risk of noncardiovascular, noncancer death attributed to inflammatory diseases in the Iowa Women's Health Study
Jacobs et al.
Am. J. Clin. Nutr. 2007;85:1606-1614.
ABSTRACT
| FULL TEXT
Waist Circumference and Cardiometabolic Risk: A Consensus Statement from Shaping America's Health: Association for Weight Management and Obesity Prevention; NAASO, The Obesity Society; the American Society for Nutrition; and the American Diabetes Association
Klein et al.
Diabetes Care 2007;30:1647-1652.
FULL TEXT
Abdominal Adiposity and Mortality in Chinese Women
Zhang et al.
Arch Intern Med 2007;167:886-892.
ABSTRACT
| FULL TEXT
Comparison of Body Mass Index, Waist Circumference, and Waist/Hip Ratio in Predicting Incident Diabetes: A Meta-Analysis
Vazquez et al.
Epidemiol Rev 2007;0:mxm008v1.
ABSTRACT
| FULL TEXT
Waist circumference and cardiometabolic risk: a consensus statement from Shaping America's Health: Association for Weight Management and Obesity Prevention; NAASO, The Obesity Society; the American Society for Nutrition; and the American Diabetes Association
Klein et al.
Am. J. Clin. Nutr. 2007;85:1197-1202.
FULL TEXT
Waist circumference and waist-to-hip ratio as predictors of cardiovascular events: meta-regression analysis of prospective studies
de Koning et al.
Eur Heart J 2007;0:ehm026v1-7.
ABSTRACT
| FULL TEXT
Interactions between Insulin, Body Fat, and Insulin-Like Growth Factor Axis Proteins
Ahmed et al.
Cancer Epidemiol. Biomarkers Prev. 2007;16:593-597.
ABSTRACT
| FULL TEXT
Risk Factors for Mortality in Middle-aged Women
Tice et al.
Arch Intern Med 2006;166:2469-2477.
ABSTRACT
| FULL TEXT
Sagittal abdominal diameter: no advantage compared with other anthropometric measures as a correlate of components of the metabolic syndrome in elderly from the Hoorn Study.
Mukuddem-Petersen et al.
Am. J. Clin. Nutr. 2006;84:995-1002.
ABSTRACT
| FULL TEXT
The Effectiveness of Screening for Obesity in Primary Care: Weighing the Evidence
Wilson and McAlpine
Med Care Res Rev 2006;63:570-598.
ABSTRACT
Body fat distribution and risk of type 2 diabetes in the general population: are there differences between men and women? The MONICA/KORA Augsburg Cohort Study.
Meisinger et al.
Am. J. Clin. Nutr. 2006;84:483-489.
ABSTRACT
| FULL TEXT
The medical complications of obesity
Malnick and Knobler
QJM 2006;99:565-579.
FULL TEXT
Comparison of Anthropometric Characteristics in Predicting the Incidence of Type 2 Diabetes in the EPIC-Potsdam Study
Schulze et al.
Diabetes Care 2006;29:1921-1923.
FULL TEXT
Mortality and cardiac and vascular outcomes in extremely obese women.
McTigue et al.
JAMA 2006;296:79-86.
ABSTRACT
| FULL TEXT
Combining Risk Estimates from Observational Studies with Different Exposure Cutpoints: A Meta-analysis on Body Mass Index and Diabetes Type 2
Hartemink et al.
Am J Epidemiol 2006;163:1042-1052.
ABSTRACT
| FULL TEXT
Association of Body Mass Index and Weight Change with All-Cause Mortality in the Elderly
Corrada et al.
Am J Epidemiol 2006;163:938-949.
ABSTRACT
| FULL TEXT
Consumption of coffee is associated with reduced risk of death attributed to inflammatory and cardiovascular diseases in the Iowa Women's Health Study
Andersen et al.
Am. J. Clin. Nutr. 2006;83:1039-1046.
ABSTRACT
| FULL TEXT
Functional limitations in elderly female cancer survivors.
Sweeney et al.
JNCI J Natl Cancer Inst 2006;98:521-529.
ABSTRACT
| FULL TEXT
What aspects of body fat are particularly hazardous and how do we measure them?
Snijder et al.
Int J Epidemiol 2006;35:83-92.
FULL TEXT
Magnesium Intake and Reduced Risk of Colon Cancer in a Prospective Study of Women
Folsom and Hong
Am J Epidemiol 2006;163:232-235.
ABSTRACT
| FULL TEXT
Association of Overweight with Breast Cancer Survival
Tao et al.
Am J Epidemiol 2006;163:101-107.
ABSTRACT
| FULL TEXT
Are waist circumference and body mass index independently associated with cardiovascular disease risk in Chinese adults?
Wildman et al.
Am. J. Clin. Nutr. 2005;82:1195-1202.
ABSTRACT
| FULL TEXT
Obesity in older adults: technical review and position statement of the American Society for Nutrition and NAASO, The Obesity Society
Villareal et al.
Am. J. Clin. Nutr. 2005;82:923-934.
ABSTRACT
| FULL TEXT
Inactivity, exercise, and visceral fat. STRRIDE: a randomized, controlled study of exercise intensity and amount
Slentz et al.
J. Appl. Physiol. 2005;99:1613-1618.
ABSTRACT
| FULL TEXT
Cardiovascular Mortality in Overweight Subjects: The Key Role of Associated Risk Factors
Thomas et al.
Hypertension 2005;46:654-659.
ABSTRACT
| FULL TEXT
Enlarged Waist Combined With Elevated Triglycerides Is a Strong Predictor of Accelerated Atherogenesis and Related Cardiovascular Mortality in Postmenopausal Women
Tanko et al.
Circulation 2005;111:1883-1890.
ABSTRACT
| FULL TEXT
Comparison of abdominal adiposity and overall obesity in predicting risk of type 2 diabetes among men
Wang et al.
Am. J. Clin. Nutr. 2005;81:555-563.
ABSTRACT
| FULL TEXT
Sleep {middle dot} 6: Obstructive sleep apnoea/hypopnoea syndrome and hypertension
Robinson et al.
Thorax 2004;59:1089-1094.
ABSTRACT
| FULL TEXT
Fish Intake, Marine Omega-3 Fatty Acids, and Mortality in a Cohort of Postmenopausal Women
Folsom and Demissie
Am J Epidemiol 2004;160:1005-1010.
ABSTRACT
| FULL TEXT
The Metabolic Syndrome in Obese Postmenopausal Women: Relationship to Body Composition, Visceral Fat, and Inflammation
You et al.
J. Clin. Endocrinol. Metab. 2004;89:5517-5522.
ABSTRACT
| FULL TEXT
Risk Factors for Breast Cancer in Elderly Women
Sweeney et al.
Am J Epidemiol 2004;160:868-875.
ABSTRACT
| FULL TEXT
Body Mass Index, Waist Circumference, and Clustering of Cardiovascular Disease Risk Factors in a Biracial Sample of Children and Adolescents
Katzmarzyk et al.
Pediatrics 2004;114:e198-e205.
ABSTRACT
| FULL TEXT
Adherence to the AICR Cancer Prevention Recommendations and Subsequent Morbidity and Mortality in the Iowa Women's Health Study Cohort
Cerhan et al.
Cancer Epidemiol. Biomarkers Prev. 2004;13:1114-1120.
ABSTRACT
| FULL TEXT
Obesity Over the Life Course
Mizuno et al.
Sci Aging Knowl Environ 2004;2004:re4-re4.
ABSTRACT
| FULL TEXT
Physical Activity and Reduced Risk of Incident Sporadic Colorectal Adenomas: Observational Support for Mechanisms Involving Energy Balance and Inflammation Modulation
Hauret et al.
Am J Epidemiol 2004;159:983-992.
ABSTRACT
| FULL TEXT
Genome-Wide Linkage to Chromosome 6 for Waist Circumference in the Framingham Heart Study
Fox et al.
Diabetes 2004;53:1399-1402.
ABSTRACT
| FULL TEXT
Body-Weight Change and Physical Functioning Among Young Old Adults
Jenkins
J Aging Health 2004;16:248-266.
ABSTRACT
Screening and Interventions for Obesity in Adults: Summary of the Evidence for the U.S. Preventive Services Task Force
McTigue et al.
ANN INTERN MED 2003;139:933-949.
ABSTRACT
| FULL TEXT
Waist-to-Hip Ratio and Breast Cancer Mortality
Borugian et al.
Am J Epidemiol 2003;158:963-968.
ABSTRACT
| FULL TEXT
Echocardiographic Epicardial Adipose Tissue Is Related to Anthropometric and Clinical Parameters of Metabolic Syndrome: A New Indicator of Cardiovascular Risk
Iacobellis et al.
J. Clin. Endocrinol. Metab. 2003;88:5163-5168.
ABSTRACT
| FULL TEXT
Appropriateness of anthropometric obesity indicators in assessment of coronary heart disease risk among Finnish men and women
Silventoinen et al.
Scand J Public Health 2003;31:283-290.
ABSTRACT
Diabetes and Abnormal Glucose Tolerance in Women With Previous Gestational Diabetes
Albareda et al.
Diabetes Care 2003;26:1199-1205.
ABSTRACT
| FULL TEXT
Metabolic Syndrome and Development of Diabetes Mellitus: Application and Validation of Recently Suggested Definitions of the Metabolic Syndrome in a Prospective Cohort Study
Laaksonen et al.
Am J Epidemiol 2002;156:1070-1077.
ABSTRACT
| FULL TEXT
Coronary atherogenic risk factors in women
Stangl et al.
Eur Heart J 2002;23:1738-1752.
FULL TEXT
Mortality risk associated with rheumatoid arthritis in a prospective cohort of older women: results from the Iowa Women's Health Study
Mikuls et al.
Ann Rheum Dis 2002;61:994-999.
ABSTRACT
| FULL TEXT
Anthropometric Characteristics, Physical Activity, and Risk of Non-Hodgkin's Lymphoma Subtypes and B-Cell Chronic Lymphocytic Leukemia: A Prospective Study
Cerhan et al.
Am J Epidemiol 2002;156:527-535.
ABSTRACT
| FULL TEXT
Abdominal obesity is associated with increased risk of acute coronary events in men
Lakka et al.
Eur Heart J 2002;23:706-713.
ABSTRACT
| FULL TEXT
The impact of obesity on the short-term andlong-term outcomes after percutaneous coronary intervention: the obesity paradox?
Gruberg et al.
J Am Coll Cardiol 2002;39:578-584.
ABSTRACT
| FULL TEXT
Effect of Low-Fat and/or Low-Energy Diets on Anthropometric Measures in Participants of the Women's Diet Study
Djuric et al.
J. Am. Coll. Nutr. 2002;21:38-46.
ABSTRACT
| FULL TEXT
Potential for the prevention of type 2 diabetes
Eriksson et al.
Br Med Bull 2001;60:183-199.
FULL TEXT
Other Articles Noted
Evid. Based Nurs. 2001;4:E1-11.
FULL TEXT
Parental History of Diabetes Modifies the Association Between Abdominal Adiposity and Hyperglycemia
van Dam et al.
Diabetes Care 2001;24:1454-1459.
ABSTRACT
| FULL TEXT
American Diabetes Association 60th Scientific Sessions, 2000: Glucose tolerance, diabetes and cancer, glycemic control, monitoring, and related topics
Bloomgarden
Diabetes Care 2001;24:779-784.
FULL TEXT
|
