PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of amjepidLink to Publisher's site
 
Am J Epidemiol. Sep 1, 2012; 176(5): 431–442.
Published online Jul 20, 2012. doi:  10.1093/aje/kws032
PMCID: PMC3499117
Obesity and All-Cause Mortality Among Black Adults and White Adults
Sarah S. Cohen,* Lisa B. Signorello, Elizabeth L. Cope, Joseph K. McLaughlin, Margaret K. Hargreaves, Wei Zheng, and William J. Blot
* Correspondence to Dr. Sarah S. Cohen, International Epidemiology Institute, 1455 Research Boulevard, Suite 550, Rockville, MD 20850 (e-mail: sarah/at/iei.us).
Contributed by
Abbreviations: BMI, body mass index; CI, confidence interval; HR, hazard ratio; ICD-10, International Classification of Diseases, Tenth Revision; SCCS, Southern Community Cohort Study.
Received November 8, 2011; Accepted January 23, 2012.
In recent pooled analyses among whites and Asians, mortality was shown to rise markedly with increasing body mass index (BMI; weight (kg)/height (m)2), but much less is known about this association among blacks. This study prospectively examined all-cause mortality in relation to BMI among 22,014 black males, 9,343 white males, 30,810 black females, and 14,447 white females, aged 40–79 years, from the Southern Community Cohort Study, an epidemiologic cohort of largely low-income participants in 12 southeastern US states. Participants enrolled in the cohort from 2002 to 2009 and were followed up to 8.9 years. Hazard ratios and 95% confidence intervals for mortality were obtained from sex- and race-stratified Cox proportional hazards models in association with BMI at cohort entry, adjusting for age, education, income, cigarette smoking, and alcohol consumption. Elevated BMI was associated with increased mortality among whites (hazard ratios for BMI >40 vs. 20–24.9 = 1.37 (95% confidence interval (CI): 1.02, 1.84) and 1.47 (95% CI: 1.15, 1.89) for white males and white females, respectively) but not significantly among blacks (hazard ratios = 1.13 (95% CI: 0.89, 1.43) and 0.87 (95% CI: 0.72, 1.04) for black males and black females, respectively). In this large cohort, obesity in mid-to-late adulthood among blacks was not associated with the same excess mortality risk seen among whites.
Keywords: African Americans, body mass index, mortality
The rise in obesity levels in the general population over the past 3 decades (13) is expected to result in enormous health burdens and health-care costs as obesity is linked to many adverse health outcomes, including diabetes, cardiovascular disease, cancer, and overall mortality (46). Recent pooled cohort analyses have reported a J-shaped relation between body mass index (BMI) and all-cause mortality with more than doubled mortality risks among extremely obese whites (6, 7) and parallel but less pronounced risks among East Asians (8). Some previous studies have found a weaker obesity-mortality association among African Americans (914), but few studies have examined this question in large populations of African Americans, and none have been concentrated in low-income populations or in the southeastern United States where the obesity epidemic is pronounced (15). Our objective therefore was to prospectively examine the association between BMI and all-cause mortality in the Southern Community Cohort Study (SCCS), a unique cohort with a large African-American population as well as a sizeable group of socioeconomically comparable whites.
Study participants
The SCCS is a prospective cohort study assessing disparities in chronic diseases among adults in urban and rural areas in 12 southeastern US states (1618). From 2002 to 2009, nearly 86,000 adults were enrolled in the cohort, most (86%) at one of 71 participating community health centers that provide basic health services mainly to low-income and uninsured persons (19). An additional 14% of the cohort enrolled from 2004 to 2006 by responding to a mailed questionnaire sent to randomly selected residents of the same 12 states. SCCS participants were required to be 40–79 years of age, to speak English, and not to be under treatment for cancer in the 12 months preceding cohort enrollment. The enrollment protocol was designed so that overall approximately two-thirds of participants would be black. The SCCS was approved by institutional review boards at Vanderbilt University and Meharry Medical College, and all participants provided written, informed consent.
Data collection and BMI assessment
Participants completed a baseline survey (via in-person interview for community health center enrollees and a self-administered questionnaire for mail enrollees) at enrollment. This survey, available online (18), contained questions about demographic, medical, familial, lifestyle, and other participant characteristics. Race was self-reported. Current weight and height were self-reported in the baseline survey through September 2007 and, in addition, for 25% of the community health center participants, height and weight measured on the day of the baseline interview were abstracted from community health center medical records. Starting in October 2007, height and weight were measured for all community health center participants by trained interviewers using a SECA 703 digital scale (SECA Corp., Hanover, Maryland) and height rod, and waist and hip circumferences were measured using a standardized protocol with a tape measure over a single layer of clothing.
BMI was calculated as weight (kg)/height (m)2 and categorized as <18.5, 18.5–19.9, 20–22.4, 22.5–24.9 (referent, selected for comparability to existing studies (6, 7, 14)), 25–27.4, 27.5–29.9, and obesity classes I (30.0–34.9), II (35.0–39.9), and III or extreme obesity (≥40). For most analyses, BMI categories were collapsed to <20, 20–24.9 (referent), 25–29.9, 30–34.9, 35–39.9, and ≥40 to compare with other existing reports.
Mortality ascertainment
Vital status was ascertained from the Social Security Administration through February 2011, while the National Death Index provided cause of death information through December 2009. Participants were followed starting 1 year after cohort entry to avoid including deaths where disease-related weight change near the time of enrollment might bias the results. For analyses of all-cause mortality, follow-up extended through February 25, 2011 (coincident with the most recent Social Security Administration linkage) or date of death. For those whose vital status was reported as unknown by the Social Security Administration in 2011, follow-up was censored at the last SCCS contact with the participant or December 31, 2009 (latest National Death Index linkage). Using cause of death information provided by the National Death Index, we examined cause-specific mortality with follow-up ending on December 31, 2009.
Statistical analyses
Cox proportional hazards models were used to estimate hazard ratios and accompanying 95% confidence intervals for all-cause mortality separately among black participants and white participants in relation to BMI at cohort entry. Age was used as the underlying time metric. Our a priori analysis plan called for examination of risk separately among blacks and whites, although likelihood ratio tests comparing models with and without race-BMI interaction terms showed significant interaction only for women (P = 0.003; P = 0.11 among men). Interactions between sex and BMI were significant in both race groups (likelihood ratio test P = 0.02 for blacks and P = 0.04 for whites). Covariates included in all models were source of enrollment (community health center/general population); education (<9 years, 9–11 years, high school, some college, and college or postgraduate); annual household income (<$15,000, $15,000–$24,999, $25,000–$49,999, and $50,000 or more); cigarette smoking status (never, former, current <1 pack/day, current/ ≥ 1 packs/day); and alcohol consumption (0, <1, ≥1 drinks/day). Cigarette smoking was also examined in finer categories with no appreciable differences in results. Total physical activity, health insurance status, and ever use of hormone replacement therapy (women only) were examined as potential confounders, but their inclusions made no material differences in the hazard ratios and therefore were not retained in the final models.
Models limited to participants who were nonsmokers with no major chronic disease (heart attack or coronary artery bypass surgery, stroke, or cancer excluding nonmelanoma skin cancer) at baseline were also examined to reduce the potential for reverse confounding due to smoking or underlying disease processes. Models further separating the nonsmokers into never smokers and former smokers showed little evidence of differences in hazard ratios, so only the combined group of nonsmokers is presented. To assess the proportionality assumptions of the Cox models, we compared hazard ratios for the first 5 versus subsequent years. To examine potential effect modification by socioeconomic status, we stratified models by education (less than high school and high school or more) and household income (<$15,000/year and $15,000 or more per year), and models with and without interaction terms between these factors and BMI were evaluated using the likelihood ratio test.
Cause-specific categories of mortality were examined (cardiovascular disease (International Classification of Diseases, Tenth Revision (ICD-10), codes I00–I99), cancer (ICD-10 codes C00–C97), and all other nonexternal causes that excluded cardiovascular disease, cancer, and all ICD-10 codes beginning with S, T, V, W, X, and Y) in race- and sex-stratified models with the same set of covariates as in the all-cause mortality models.
Although relatively few participants had measured waist and hip circumferences (n = 8,319) and follow-up was shorter (maximum = 3.4 years) due to the addition of these measurements in October 2007, in exploratory analyses we examined mortality according to sex-specific quartiles of waist circumference and waist/hip ratio in race-stratified models with adjustment for sex and the other variables included in the BMI-mortality models as described above.
All analyses were conducted using SAS/STAT software, version 9.3, of the SAS System for Windows (SAS Institute, Inc., Cary, North Carolina).
A total of 85,759 individuals enrolled in the SCCS between March 2002 and September 2009. After excluding 5,017 participants (5.9%) who reported their race as other than only “white” or “black/African American,” 852 participants (1.1%) with missing height or weight values, and 3,276 participants with follow-up of less than 1 year, 76,614 participants remained for analysis. The mean age at enrollment was 51.8 years for blacks and 54.4 years for whites. Regardless of race or sex, the cohort members were generally of low income and educational status, and cigarette smoking was common, especially among men (Table 1).
Table 1.
Table 1.
Characteristics of 76,614 Southern Community Cohort Study Participants by Sex and Race, 2002–2009
Obesity (BMI >30) at entry was common in all 4 race and sex groups, with the highest prevalence (58%) in black women (Table 1). There was little difference in BMI between never smokers and former smokers and between light and heavy current smokers, but BMI was markedly lower among current compared with former/never smokers (data not shown).
During follow-up of up to 8.9 years (mean, 5.2 years), 5,427 deaths were identified. In all sex-race groups except white males, underweight individuals experienced significantly higher mortality than those who were of normal weight (Table 2; Figure 1). Among blacks, the hazard ratios for mortality were lower for those who were overweight or in obesity classes I and II compared with those of normal weight. In contrast, among whites, the lowest mortality risk occurred among those with BMI 25–29, and hazard ratios rose thereafter, reaching a 40%–50% excess among those in obesity class III.
Table 2.
Table 2.
Hazard Ratios and 95% Confidence Intervals From Race- and Sex-stratified Cox Proportional Hazards Models Examining All-Cause Mortality in Relation to Body Mass Index at Cohort Entry, Omitting the First 12 Months of Follow-up, Southern Community Cohort (more ...)
Figure 1.
Figure 1.
Hazard ratios for all-cause mortality by categories of body mass index at cohort entry for black adults and white adults by sex (females, top; males, bottom), Southern Community Cohort Study, 2002–2009. Cox proportional hazards models were adjusted (more ...)
Restricting the participants to nonsmokers not reporting cancer, heart disease, or stroke at baseline resulted in little change; hazard ratios for those with current BMI <20, 20–24.9 (referent), 25–29.9, 30–34.9, 35–39.9, and ≥40 were, respectively, 2.06 (95% confidence interval (CI): 1.53, 2.79), 1.0 (referent), 0.72 (95% CI: 0.61, 0.86), 0.66 (95% CI: 0.54, 0.80), 0.72 (95% CI: 0.58, 0.89), and 1.09 (95% CI: 0.89, 1.35) among blacks and 0.81 (95% CI: 0.35, 1.87), 1.0 (referent), 0.84 (95% CI: 0.62, 1.13), 0.85 (95% CI: 0.62, 1.17), 1.12 (95% CI: 0.79, 1.59), and 1.74 (95% CI: 1.25, 2.41) among whites.
Excess mortality associated with low BMI of <18.5 tended to be less pronounced in the ≥5-year follow-up period than in the period 1–4.9 years. Otherwise, few consistent or marked changes were apparent in the BMI-mortality patterns between the 2 time periods (Table 3).
Table 3.
Table 3.
Hazard Ratios and 95% Confidence Intervals From Race- and Sex-stratified Cox Proportional Hazards Models Examining All-Cause Mortality in Relation to Body Mass Index at Cohort Entry, Omitting the First 12 Months of Follow-up, Stratified by Follow-up Time (more ...)
The association between BMI and all-cause mortality differed very little for black males or black females when stratified by age at cohort entry (<55 vs. ≥55 years) (Table 3). Among whites, the hazard ratios for mortality associated with extreme obesity were somewhat higher in males and females aged ≥55 years versus <55 years (Table 3).
In analyses stratified by education or income, the hazard ratios associated with obesity tended to be lower among those with lower socioeconomic status in all sex-race groups (Table 4). Interaction terms between income and BMI, however, were significant only for black men (P = 0.01) and borderline for black women (P = 0.06), and interactions with education were significant only in black women (P = 0.03).
Table 4.
Table 4.
Hazard Ratios and 95% Confidence Intervals From Race- and Sex-stratified Cox Proportional Hazards Models Examining All-Cause Mortality in Relation to Body Mass Index at Cohort Entry, Omitting the First 12 Months of Follow-up, Stratified by Measures of (more ...)
Cancer and then heart disease were the leading causes of death among both blacks and whites. Among other causes, human immunodeficiency virus (HIV)/acquired immune deficiency syndrome (AIDS), diabetes, and cerebrovascular disease were the most common in blacks, and chronic lower respiratory diseases, diabetes, and liver disease were most common among whites. Increased body size was positively associated with death from cardiovascular disease in all sex-race groups, with higher hazard ratios among whites compared with blacks in the highest BMI categories (hazard ratios (HRs) for BMI >40 vs. 20–24.9 = 1.40, 2.10, 1.17, and 2.62 for black males, white males, black females, and white females, respectively) (Table 5). Cancer mortality was significantly elevated among white males but not black males with extreme obesity, while obesity was not associated with increased risk of cancer mortality in either black women or white women (Table 5).
Table 5.
Table 5.
Hazard Ratios and 95% Confidence Intervals From Race- and Sex-stratified Cox Proportional Hazards Models Examining Cause-specific Mortality in Relation to Body Mass Index at Cohort Entry, Omitting the First 12 Months of Follow-up, Southern Community Cohort (more ...)
Baseline waist and hip circumferences were available for 4,977 black participants and 3,342 white participants, 178 of whom died during follow-up. Waist circumference was strongly correlated with BMI at cohort entry (Pearson's correlation coefficient (r) = 0.82, P < 0.001), while the waist/hip ratio was less so (r = 0.22, P < 0.001) overall, with slightly higher correlations with BMI among whites (r = 0.25, P < 0.001 for the waist/hip ratio; r = 0.84, P < 0.001 for waist circumference) than among blacks (r = 0.21, P < 0.001 for the waist/hip ratio; r = 0.81, P < 0.001 for the waist circumference). Mortality hazard ratios were significantly increased among white participants for the highest versus lowest quartile of waist circumference (HR = 2.09, 95% CI: 1.01, 4.35) and nonsignificantly for the waist/hip ratio (HR = 1.29, 95% CI: 0.63, 2.63); among blacks, neither metric was associated with increased mortality (Table 6).
Table 6.
Table 6.
Hazard Ratios and 95% Confidence Intervals From Race-stratified Cox Proportional Hazards Models Examining All-Cause Mortality in Relation to Quartiles of Waist Circumference and Waist/Hip Ratio, Southern Community Cohort Study, 2002–2009
In this follow-up of a large, low-income population of black adults and white adults among whom obesity is common, the association between adult BMI and all-cause mortality differed by race. Being obese at cohort entry was not associated with elevated mortality among blacks; indeed, the lowest hazard ratios were observed among those with BMI of 30–34.9, and hazard ratios were near or even below 1.0 among those with extreme obesity. Among socioeconomically comparable whites, however, extreme obesity was associated with mortality increases up to 50% higher than among normal weight individuals.
Only a few cohort studies have had adequate samples of both blacks and whites to compare BMI–all-cause mortality patterns by race. This report includes one of the largest populations of blacks (nearly 53,000) thus far studied; further, the nearly 24,000 whites of similar socioeconomic status in the SCCS provided a comparison group to examine patterns across race while minimizing socioeconomic-related confounding. In the American Cancer Society's Cancer Prevention Study II that included 12,000 blacks, nonsmokers with no history of disease were found to have a significantly increased mortality risk among whites with extreme obesity (HR = 2.58 for males and 2.00 for females), but the association was weaker and nonsignificant among black males (HR = 1.35) and females (HR = 1.21) (20). In the National Institutes of Health (NIH)-AARP cohort of adults aged 50–71 years, including 20,200 blacks, associations between BMI and mortality were also lower among blacks than whites (HRs for BMI >40 were 1.68 for black males, 1.82 for white males, 1.70 for black females, and 1.95 for white females) (9). In a combined analysis of the First National Health and Nutrition Examination Survey Epidemiologic Follow-up Study and the National Health Interview Survey populations (including 19,000 blacks), the BMI associated with the lowest mortality risk was 3.1 kg/m2 higher among black men than white men and 1.5 kg/m2 higher among black women than white women (10). Hence, the emerging pattern is generally consistent with our findings of a weaker association between mid-to-later-life BMI and all-cause mortality among blacks than whites. However, the Black Women's Health Study reported elevated mortality among 51,695 black women for all BMI categories of 25 or higher with the highest hazard ratio observed in extremely obese black women (HR = 2.19) (14), a finding more in line with results from recent pooled analyses of whites (6, 7) than other cohort studies with large black populations.
The reasons for differing adult BMI-mortality patterns between blacks and whites are unknown. Socioeconomic differences have been postulated (12, 13) but seem unlikely to account for elevated BMI as a risk factor only for whites in this study, because income and education distributions were fairly similar between black participants and white participants (and residual differences were adjusted in the analysis). Among both blacks and whites, however, we did observe that mortality risks associated with obesity tended to be lower among those with lower socioeconomic status, perhaps because other detriments to health are more prominent among low income populations. Similar differences by education were also observed among black women in the Black Women's Health Study, where excess mortality among the obese was limited to those with greater than 12 years of education (14). Other factors related to overall mortality that might differ by race could play a role in the black-white difference in the BMI-mortality relation. We examined the effect of cigarette smoking by adjusting for smoking in the analyses and by restricting analyses to nonsmokers, but in both, the differential BMI mortality patterns between blacks and whites persisted.
In cause-specific mortality analyses, the most pronounced differences between blacks and whites were seen for cardiovascular disease mortality, where more than 2-fold increases were seen in whites in obesity classes II and III, while only slight and nonsignificant increases were observed in blacks of similarly elevated BMI. The stronger association between BMI and cardiovascular disease (compared with cancer or other combined causes of death) has been observed in previous large studies of primarily white individuals (6, 7, 20), as well black women (14). The difference seems likely to be due to stronger correlations between obesity and factors directly associated with increased risk of cardiovascular disease (more so than for cancer or other nonexternal causes) including dyslipidemia, hypertension, and insulin resistance (21). We have previously reported that the prevalence of diabetes, a strong cardiovascular disease risk factor, rose markedly with increasing BMI (22). In ongoing analyses, we have also observed a higher prevalence of atrial fibrillation, another cardiovascular disease risk factor, among SCCS participants with high BMI (Loren Lipworth, Vanderbilt University, personal communication, 2011). Notably, for both our analyses of diabetes and atrial fibrillation within the SCCS, the association with obesity was stronger among whites than blacks, which may help to explain the larger racial difference seen for cardiovascular disease mortality than for cancer or other causes.
For all cancers, the differential pattern by race in the BMI-mortality association was evident only among males, but this finding should be viewed as preliminary given the relatively small number of cancers among whites. The major cause of cancer death among SCCS participants was lung cancer, which tends to be inversely associated with obesity (4). Thus, the influence of lung cancer on total cancer mortality likely dampened the association with obesity and accentuated the difference between the cardiovascular disease-BMI and cancer-BMI associations. Further, the absence of a strong association between cancer mortality and BMI tends to minimize the possibility for a racial difference, further accentuating the strong racial difference in cardiovascular disease mortality.
The different patterns by race for the BMI-overall mortality associations, as well as the more pronounced racial difference for cardiovascular disease mortality, may indicate that equivalency of BMI does not mean equivalency of the specific body composition parameters most associated with mortality. Although BMI is highly correlated with overall body fat, the distribution of fat is not well captured by BMI (23). As blacks have been shown to have less mean visceral fat than whites at the same level of BMI (24) and because visceral fat is more strongly associated with metabolic disorders and cardiovascular disease than subcutaneous fat (23), measures of adiposity such as waist circumference or waist/hip ratio may be better predictors of health outcomes than BMI, especially when examining populations with diverse racial backgrounds (2527). In the SCCS, despite having measured data on waist circumference and waist/hip ratio for only a small subset of the cohort with limited follow-up, we observed that waist circumference was significantly associated with all-cause mortality only among whites, similar to the associations we observed with BMI, whereas trends in hazard ratios associated with waist circumference among blacks were flat. Thus, while BMI may be a less sensitive indicator of the body size characteristics (i.e., abdominal obesity) predictive of increased mortality among blacks, further study is needed to help identify factors underlying the racial differences in mortality patterns observed here and in other studies, as well as to clarify whether excess weight is actually less detrimental to health in blacks.
Future research would also benefit from the assessment of differences between blacks and whites in genetic variants thought to be associated with obesity and potential mortality. Within the SCCS, we recently reported that mean serum levels of adiponectin, an adipose tissue-derived protein that plays a critical role in several physiologic pathways related to disease risk (28), decreased monotonically with increasing BMI among white but not black women (29). Furthermore, we found that single nucleotide polymorphisms in adiponectin-related genes were associated with the serum levels only among whites (30). These preliminary findings suggest that genetically determined biologic attributes may be contributing to the differing patterns between obesity and overall mortality, but additional study is needed to clarify the roles of allelic variation and the potential mechanisms involved.
Limitations of this study first include the use of self-reported height and weight for a large proportion of participants. While height tends to be overreported and weight underreported (31), data from the 1999 to 2004 National Health and Nutrition Examination Survey show that, despite errors in self-report, BMI categories based on self-reported values still generally demonstrate good agreement with BMI categories from measured values (32). Furthermore, in the SCCS, BMI values calculated from self-reported height and weight were highly correlated with values calculated from abstracted community health center medical records overall (n = 14,000; Pearson's correlation > 0.95) and within strata of race, income, and education, indicating that the self-reported values are generally of high quality. An additional limitation is the difficulty in controlling for existing disease, particularly with the relatively short follow-up currently available in the SCCS. It is likely that the higher mortality observed in underweight participants at least partially reflects preexisting disease processes. We attempted to address this issue by excluding the first 12 months of follow-up, but as the cohort is followed for longer periods, we anticipate that the high risks associated with lower weight will begin to dissipate, a trend that has already been seen in follow-up greater than 5 years after cohort entry.
This study also has several notable strengths. First, although the SCCS population is not reflective of the socioeconomic or racial distributions in the general US population because of the recruitment strategy through community health centers and the resulting overrepresentation of low-income individuals, it is a unique cohort in which to study health effects in blacks compared with whites because of both the large number of blacks and the comparability of socioeconomic status between the racial groups. The SCCS data add an important new dimension to the existing body of literature that for the most part has examined associations between obesity and mortality in middle or upper income cohorts, while the SCCS by contrast is composed of largely low-income individuals among whom obesity is more prevalent. Second, because of the large size of this cohort and the extensive data on smoking collected during the baseline questionnaire, we were able to carefully control for smoking, an important confounder of the mortality-obesity relation.
In summary, we found that racial differences in BMI-mortality associations exist between African Americans and whites of similarly low socioeconomic levels. These findings should stimulate additional research to untangle and identify the complex mechanisms underlying the observed racial differences and help in tailoring strategies to combat the adverse health effects of obesity in all population groups.
ACKNOWLEDGMENTS
Author affiliations: International Epidemiology Institute, Rockville, Maryland (Sarah S. Cohen, Lisa B. Signorello, Elizabeth L. Cope, Joseph K. McLaughlin, William J. Blot); Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center and Vanderbilt-Ingram Cancer Center, Nashville, Tennessee (Lisa B. Signorello, Joseph K. McLaughlin, Wei Zheng, William J. Blot); and Department of Internal Medicine, Meharry Medical College, Nashville, Tennessee (Margaret K. Hargreaves).
The Southern Community Cohort Study is funded by grant R01 CA92447 from the National Cancer Institute, including special allocations from the American Recovery and Reinvestment Act (3R01 CA092447-08S1). This project was also funded in part by grant OP05-0927-DR1 from Susan G. Komen for the Cure. Partial support for M. K. H. was provided by grants 5P60 DK20593-24 and 5U01 CA114641-05 from the National Institutes of Health.
Conflict of interest: none declared.
1. Flegal KM, Carroll MD, Ogden CL, et al. Prevalence and trends in obesity among US adults, 1999–2008. JAMA. 2010;303(3):235–241. [PubMed]
2. Ogden CL, Carroll MD, Curtin LR, et al. Prevalence of overweight and obesity in the United States, 1999–2004. JAMA. 2006;295(13):1549–1555. [PubMed]
3. Flegal KM, Carroll MD, Kuczmarski RJ, et al. Overweight and obesity in the United States: prevalence and trends, 1960–1994. Int J Obes Relat Metab Disord. 1998;22(1):39–47. [PubMed]
4. Calle EE, Thun MJ. Obesity and cancer. Oncogene. 2004;23(38):6365–6378. [PubMed]
5. Eckel RH, York DA, Rössner S, et al. Prevention Conference VII: obesity, a worldwide epidemic related to heart disease and stroke: executive summary. American Heart Association. Circulation. 2004;110(18):2968–2975. [PubMed]
6. Berrington de Gonzalez A, Hartge P, Cerhan JR, et al. Body-mass index and mortality among 1.46 million white adults. N Engl J Med. 2010;363(23):2211–2219. [PMC free article] [PubMed]
7. 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. Prospective Studies Collaboration. Lancet. 2009;373(9669):1083–1096. [PMC free article] [PubMed]
8. Zheng W, McLerran DF, Rolland B, et al. Association between body-mass index and risk of death in more than 1 million Asians. N Engl J Med. 2011;364(8):719–729. [PubMed]
9. Adams KF, Schatzkin A, Harris TB, et al. Overweight, obesity, and mortality in a large prospective cohort of persons 50 to 71 years old. N Engl J Med. 2006;355(8):763–778. [PubMed]
10. Durazo-Arvizu R, Cooper RS, Luke A, et al. Relative weight and mortality in U.S. blacks and whites: findings from representative national population samples. Ann Epidemiol. 1997;7(6):383–395. [PubMed]
11. Reis JP, Araneta MR, Wingard DL, et al. Overall obesity and abdominal adiposity as predictors of mortality in U.S. white and black adults. Ann Epidemiol. 2009;19(2):134–142. [PubMed]
12. Stevens J. Obesity and mortality in Africans-Americans. Nutr Rev. 2000;58(11):346–353. [PubMed]
13. Fontaine KR, Redden DT, Wang C, et al. Years of life lost due to obesity. JAMA. 2003;289(2):187–193. [PubMed]
14. Boggs DA, Rosenberg L, Cozier YC, et al. General and abdominal obesity and risk of death among black women. N Engl J Med. 2011;365(10):901–908. [PMC free article] [PubMed]
15. Centers for Disease Control and Prevention. Behavioral Risk Factor Surveillance System Survey Data. Atlanta, GA: US Department of Health and Human Services; 2007.
16. Signorello LB, Hargreaves MK, Blot WJ. The Southern Community Cohort Study: investigating health disparities. J Health Care Poor Underserved. 2010;21(1 suppl):26–37. [PMC free article] [PubMed]
17. Signorello LB, Hargreaves MK, Steinwandel MD, et al. Southern Community Cohort Study: establishing a cohort to investigate health disparities. J Natl Med Assoc. 2005;97(7):972–979. [PMC free article] [PubMed]
18. Southern Community Cohort Study. Nashville, TN: Vanderbilt-Ingram Cancer Center; 2009. (http://www.southerncommunitystudy.org/InfoResearch/Information.htm. ). (Accessed January 19, 2012)
19. Hargreaves MK, Arnold C, Blot WJ. Community health centers: their role in the treatment of minorities in health disparities research. In: Satcher D, Pamies R, editors. Multicultural Medicine and Health Disparities. New York, NY: McGraw-Hill; 2006. pp. 485–494.
20. Calle EE, Thun MJ, Petrelli JM, et al. Body-mass index and mortality in a prospective cohort of U.S. adults. N Engl J Med. 1999;341(15):1097–1105. [PubMed]
21. Ogden CL, Yanovski SZ, Carroll MD, et al. The epidemiology of obesity. Gastroenterology. 2007;132(6):2087–2102. [PubMed]
22. Signorello LB, Schlundt DG, Cohen SS, et al. Comparing diabetes prevalence between African Americans and whites of similar socioeconomic status. Am J Public Health. 2007;97(12):2260–2267. [PubMed]
23. Snijder MB, van Dam RM, Visser M, et al. What aspects of body fat are particularly hazardous and how do we measure them? Int J Epidemiol. 2006;35(1):83–92. [PubMed]
24. Lovejoy JC, de la Bretonne JA, Klemperer M, et al. Abdominal fat distribution and metabolic risk factors: effects of race. Metabolism. 1996;45(9):1119–1124. [PubMed]
25. Simpson JA, MacInnis RJ, Peeters A, et al. A comparison of adiposity measures as predictors of all-cause mortality: the Melbourne Collaborative Cohort Study. Obesity (Silver Spring) 2007;15(4):994–1003. [PubMed]
26. Welborn TA, Dhaliwal SS. Preferred clinical measures of central obesity for predicting mortality. Eur J Clin Nutr. 2007;61(12):1373–1379. [PubMed]
27. Czernichow S, Kengne AP, Stamatakis E, et al. Body mass index, waist circumference and waist-hip ratio: which is the better discriminator of cardiovascular disease mortality risk?: evidence from an individual-participant meta-analysis of 82 864 participants from nine cohort studies. Obes Rev. 2011;12(9):680–687. [PubMed]
28. Chandran M, Phillips SA, Ciaraldi T, et al. Adiponectin: more than just another fat cell hormone? Diabetes Care. 2003;26(8):2442–2450. [PubMed]
29. Cohen SS, Gammon MD, Signorello LB, et al. Serum adiponectin in relation to body mass index and other correlates in black and white women. Ann Epidemiol. 2011;21(2):86–94. [PMC free article] [PubMed]
30. Cohen SS, Gammon MD, North KE, et al. ADIPOQ, ADIPOR1, and ADIPOR2 polymorphisms in relation to serum adiponectin levels and BMI in black and white women. Obesity (Silver Spring) 2011;19(10):2053–2062. [PMC free article] [PubMed]
31. Gorber SC, Tremblay M, Moher D, et al. A comparison of direct vs. self-report measures for assessing height, weight and body mass index: a systematic review. Obes Rev. 2007;8(4):307–326. [PubMed]
32. Craig BM, Adams AK. Accuracy of body mass index categories based on self-reported height and weight among women in the United States. Matern Child Health J. 2009;13(4):489–496. [PMC free article] [PubMed]
Articles from American Journal of Epidemiology are provided here courtesy of
Oxford University Press