Barry I. Graubard

Association of All-Cause Mortality With Overweight and Obesity Using Standard Body Mass Index Categories

IMPORTANCE Estimates of the relative mortality risks associated with normal weight, overweight, and obesity may help to inform decision making in the clinical setting. OBJECTIVE To perform a systematic review of reported hazard ratios (HRs) of all-cause mortality for overweight and obesity relative to normal weight in the general population. DATA SOURCES PubMed and EMBASE electronic databases were searched through September 30, 2012, without language restrictions. STUDY SELECTION Articles that reported HRs for all-cause mortality using standard body mass index (BMI) categories from prospective studies of general populations of adults were selected by consensus among multiple reviewers. Studies were excluded that used nonstandard categories or that were limited to adolescents or to those with specific medical conditions or to those undergoing specific procedures. PubMed searches yielded 7034 articles, of which 141 (2.0%) were eligible. An EMBASE search yielded 2 additional articles. After eliminating overlap, 97 studies were retained for analysis, providing a combined sample size of more than 2.88 million individuals and more than 270,000 deaths. DATA EXTRACTION Data were extracted by 1 reviewer and then reviewed by 3 independent reviewers. We selected the most complex model available for the full sample and used a variety of sensitivity analyses to address issues of possible overadjustment (adjusted for factors in causal pathway) or underadjustment (not adjusted for at least age, sex, and smoking). RESULTS Random-effects summary all-cause mortality HRs for overweight (BMI of 25-<30), obesity (BMI of ≥30), grade 1 obesity (BMI of 30-<35), and grades 2 and 3 obesity (BMI of ≥35) were calculated relative to normal weight (BMI of 18.5-<25). The summary HRs were 0.94 (95% CI, 0.91-0.96) for overweight, 1.18 (95% CI, 1.12-1.25) for obesity (all grades combined), 0.95 (95% CI, 0.88-1.01) for grade 1 obesity, and 1.29 (95% CI, 1.18-1.41) for grades 2 and 3 obesity. These findings persisted when limited to studies with measured weight and height that were considered to be adequately adjusted. The HRs tended to be higher when weight and height were self-reported rather than measured. CONCLUSIONS AND RELEVANCE Relative to normal weight, both obesity (all grades) and grades 2 and 3 obesity were associated with significantly higher all-cause mortality. Grade 1 obesity overall was not associated with higher mortality, and overweight was associated with significantly lower all-cause mortality. The use of predefined standard BMI groupings can facilitate between-study comparisons.

Prevalence of Oral HPV Infection in the United States, 2009-2010

CONTEXT Human papillomavirus (HPV) infection is the principal cause of a distinct form of oropharyngeal squamous cell carcinoma that is increasing in incidence among men in the United States. However, little is known about the epidemiology of oral HPV infection. OBJECTIVE To determine the prevalence of oral HPV infection in the United States. DESIGN, SETTING, AND PARTICIPANTS A cross-sectional study was conducted as part of the National Health and Nutrition Examination Survey (NHANES) 2009-2010, a statistically representative sample of the civilian noninstitutionalized US population. Men and women aged 14 to 69 years examined at mobile examination centers were eligible. Participants (N = 5579) provided a 30-second oral rinse and gargle with mouthwash. For detection of HPV types, DNA purified from oral exfoliated cells was evaluated by polymerase chain reaction and type-specific hybridization. Demographic and behavioral data were obtained by standardized interview. Statistical analyses used NHANES sample weights to provide weighted prevalence estimates for the US population. MAIN OUTCOME MEASURES Prevalence of oral HPV infection. RESULTS The prevalence of oral HPV infection among men and women aged 14 to 69 years was 6.9% (95% CI, 5.7%-8.3%) and of HPV type 16 was 1.0% (95% CI, 0.7%-1.3%). Oral HPV infection followed a bimodal pattern with respect to age, with peak prevalence among individuals aged 30 to 34 years (7.3%; 95% CI, 4.6%-11.4%) and 60 to 64 years (11.4%; 95% CI, 8.5%-15.1%). Men had a significantly higher prevalence than women for any oral HPV infection (10.1% [95% CI, 8.3%-12.3%] vs 3.6% [95% CI, 2.6%-5.0%], P < .001; unadjusted prevalence ratio [PR], 2.80 [95% CI, 2.02-3.88]). Infection was less common among those without vs those with a history of any type of sexual contact (0.9% [95% CI, 0.4%-1.8%] vs 7.5% [95% CI, 6.1%-9.1%], P < .001; PR, 8.69 [95% CI, 3.91-19.31]) and increased with number of sexual partners (P < .001 for trend) and cigarettes smoked per day (P < .001 for trend). Associations with age, sex, number of sexual partners, and current number of cigarettes smoked per day were independently associated with oral HPV infection in multivariable models. CONCLUSION Among men and women aged 14 to 69 years in the United States, the overall prevalence of oral HPV infection was 6.9%, and the prevalence was higher among men than among women.

Comparisons of percentage body fat, body mass index, waist circumference, and waist-stature ratio in adults

BACKGROUND Body mass index (BMI), waist circumference (WC), and the waist-stature ratio (WSR) are considered to be possible proxies for adiposity. OBJECTIVE The objective was to investigate the relations between BMI, WC, WSR, and percentage body fat (measured by dual-energy X-ray absorptiometry) in adults in a large nationally representative US population sample from the National Health and Nutrition Examination Survey (NHANES). DESIGN BMI, WC, and WSR were compared with percentage body fat in a sample of 12,901 adults. RESULTS WC, WSR, and BMI were significantly more correlated with each other than with percentage body fat (P < 0.0001 for all sex-age groups). Percentage body fat tended to be significantly more correlated with WC than with BMI in men but significantly more correlated with BMI than with WC in women (P < 0.0001 except in the oldest age group). WSR tended to be slightly more correlated with percentage body fat than was WC. Percentile values of BMI, WC, and WSR are shown that correspond to percentiles of percentage body fat increments of 5 percentage points. More than 90% of the sample could be categorized to within one category of percentage body fat by each measure. CONCLUSIONS BMI, WC, and WSR perform similarly as indicators of body fatness and are more closely related to each other than with percentage body fat. These variables may be an inaccurate measure of percentage body fat for an individual, but they correspond fairly well overall with percentage body fat within sex-age groups and distinguish categories of percentage body fat.

Meat Intake and Mortality: A Prospective Study of Over Half a Million People

BACKGROUND High intakes of red or processed meat may increase the risk of mortality. Our objective was to determine the relations of red, white, and processed meat intakes to risk for total and cause-specific mortality. METHODS The study population included the National Institutes of Health-AARP (formerly known as the American Association of Retired Persons) Diet and Health Study cohort of half a million people aged 50 to 71 years at baseline. Meat intake was estimated from a food frequency questionnaire administered at baseline. Cox proportional hazards regression models estimated hazard ratios (HRs) and 95% confidence intervals (CIs) within quintiles of meat intake. The covariates included in the models were age, education, marital status, family history of cancer (yes/no) (cancer mortality only), race, body mass index, 31-level smoking history, physical activity, energy intake, alcohol intake, vitamin supplement use, fruit consumption, vegetable consumption, and menopausal hormone therapy among women. Main outcome measures included total mortality and deaths due to cancer, cardiovascular disease, injuries and sudden deaths, and all other causes. RESULTS There were 47 976 male deaths and 23 276 female deaths during 10 years of follow-up. Men and women in the highest vs lowest quintile of red (HR, 1.31 [95% CI, 1.27-1.35], and HR, 1.36 [95% CI, 1.30-1.43], respectively) and processed meat (HR, 1.16 [95% CI, 1.12-1.20], and HR, 1.25 [95% CI, 1.20-1.31], respectively) intakes had elevated risks for overall mortality. Regarding cause-specific mortality, men and women had elevated risks for cancer mortality for red (HR, 1.22 [95% CI, 1.16-1.29], and HR, 1.20 [95% CI, 1.12-1.30], respectively) and processed meat (HR, 1.12 [95% CI, 1.06-1.19], and HR, 1.11 [95% CI 1.04-1.19], respectively) intakes. Furthermore, cardiovascular disease risk was elevated for men and women in the highest quintile of red (HR, 1.27 [95% CI, 1.20-1.35], and HR, 1.50 [95% CI, 1.37-1.65], respectively) and processed meat (HR, 1.09 [95% CI, 1.03-1.15], and HR, 1.38 [95% CI, 1.26-1.51], respectively) intakes. When comparing the highest with the lowest quintile of white meat intake, there was an inverse association for total mortality and cancer mortality, as well as all other deaths for both men and women. CONCLUSION Red and processed meat intakes were associated with modest increases in total mortality, cancer mortality, and cardiovascular disease mortality.

Metabolic syndrome increases the risk of primary liver cancer in the United States: A study in the SEER‐medicare database

Incidence rates of hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) have increased in the United States. Metabolic syndrome is recognized as a risk factor for HCC and a postulated one for ICC. The magnitude of risk, however, has not been investigated on a population level in the United States. We therefore examined the association between metabolic syndrome and the development of these cancers. All persons diagnosed with HCC and ICC between 1993 and 2005 were identified in the Surveillance, Epidemiology, and End Results (SEER)‐Medicare database. For comparison, a 5% sample of individuals residing in the same regions as the SEER registries of the cases was selected. The prevalence of metabolic syndrome as defined by the U.S. National Cholesterol Education Program Adult Treatment Panel III criteria, and other risk factors for HCC (hepatitis B virus, hepatitis C virus, alcoholic liver disease, liver cirrhosis, biliary cirrhosis, hemochromatosis, Wilsons disease) and ICC (biliary cirrhosis, cholangitis, cholelithiasis, choledochal cysts, hepatitis B virus, hepatitis C virus, alcoholic liver disease, cirrhosis, inflammatory bowel disease) were compared among persons who developed cancer and those who did not. Logistic regression was used to calculate odds ratios and 95% confidence intervals. The inclusion criteria were met by 3649 HCC cases, 743 ICC cases, and 195,953 comparison persons. Metabolic syndrome was significantly more common among persons who developed HCC (37.1%) and ICC (29.7%) than the comparison group (17.1%, P < 0.0001). In adjusted multiple logistic regression analyses, metabolic syndrome remained significantly associated with increased risk of HCC (odds ratio = 2.13; 95% confidence interval = 1.96‐2.31, P < 0.0001) and ICC (odds ratio = 1.56; 95% confidence interval = 1.32‐1.83, P < 0.0001). Conclusion: Metabolic syndrome is a significant risk factor for development of HCC and ICC in the general U.S. population. (HEPATOLOGY 2011;)

A Large Prospective Study of Meat Consumption and Colorectal Cancer Risk: An Investigation of Potential Mechanisms Underlying this Association

Although the relation between red and processed meat intake and colorectal cancer has been reported in several epidemiologic studies, very few investigated the potential mechanisms. This study examined multiple potential mechanisms in a large U.S. prospective cohort with a detailed questionnaire on meat type and meat cooking methods linked to databases for estimating intake of mutagens formed in meats cooked at high temperatures (heterocyclic amines, polycyclic aromatic hydrocarbons), heme iron, nitrate, and nitrite. During 7 years of follow-up, 2,719 colorectal cancer cases were ascertained from a cohort of 300,948 men and women. The hazard ratios (HR) and 95% confidence intervals (95% CI) comparing the fifth to the first quintile for both red (HR, 1.24; 95% CI, 1.09-1.42; P(trend) < 0.001) and processed meat (HR, 1.16; 95% CI, 1.01-1.32; P(trend) = 0.017) intakes indicated an elevated risk for colorectal cancer. The potential mechanisms for this relation include heme iron (HR, 1.13; 95% CI, 0.99-1.29; P(trend) = 0.022), nitrate from processed meats (HR, 1.16; 95% CI, 1.02-1.32; P(trend) = 0.001), and heterocyclic amine intake [HR, 1.19; 95% CI, 1.05-1.34; P(trend) < 0.001 for 2-amino-3,8-dimethylimidazo[4,5-f]quinoxaline (MeIQx) and HR, 1.17; 95% CI, 1.05-1.29; P(trend) <0.001 for 2-amino-3,4,8-trimethylimidazo[4,5-f]quinoxaline (DiMeIQx)]. In general, the elevated risks were higher for rectal cancer than for colon cancer, with the exception of MeIQx and DiMeIQx, which were only associated with colon cancer. In conclusion, we found a positive association for red and processed meat intake and colorectal cancer; heme iron, nitrate/nitrite, and heterocyclic amines from meat may explain these associations.

Low energy reporters vs others: a comparison of reported food intakes.

Objective: To partition the food reports of low energy reporters (LERs) and non-LERs into four aspects—tendency to report a given food, frequency of reports per user, portion sizes per mention, and the qualitative (low-fat, low-sugar, low-energy) differences of the reports—in order to determine what differentiates them from one another.Assessment method: Two non-consecutive 24h dietary recalls. Low energy reporting was defined as energy intake lower than 80% of estimated basal metabolic rate.Setting:In-home personal interviews.Subjects: 8334 adults from a stratified, multi-stage area probability sample designed to be representative of noninstitutionlized persons residing in households in the United States.Results: Across all different types of foods, there are those food groups which LERs are less likely to report (28 of 44 food groups), those which they report less frequently when they do report them (15 of 44 groups), and those for which they report smaller quantities per mention (26 of 44). Qualitative differences in the food choices—that is, differences in fat, sugar, and/or energy content—were not so widespread (4 of 24 food groups).Conclusions: The practical application of analyses such as these is to improve the methods of gathering dietary data so that this kind of bias can be reduced. Further methodological research is needed to reduce the likelihood of respondents neglecting to mention foods and underestimating portion sizes.European Journal of Clinical Nutrition (2000) 54, 281–287

Examples of Differing Weighted and Unweighted Estimates from a Sample Survey

Abstract Unweighted estimators using data collected in a sample survey can be badly biased, whereas weighted estimators are approximately unbiased for population parameters. We present four examples using data from the 1988 National Maternal and Infant Health Survey to demonstrate that weighted and unweighted estimators can be quite different, and to show the underlying causes of such differences.

Effect of age, parity, and smoking on pregnancy outcome: A population-based study

OBJECTIVES The purpose of our study was to investigate the combined interactive effects of maternal age, parity, and smoking on pregnancy outcome. STUDY DESIGN This was a population-based Swedish study (n = 538,829). RESULTS Multiple logistic regression analysis showed that the smoking-related effect on the relative increase in the odds ratio of low birth weight and preterm delivery was significantly greater among multiparous patients than nulliparous; among multiparas, smoking increased the odds ratios for low birth weight and preterm delivery by 2.4 and 1.6; the corresponding relative increases in the odds ratios among nulliparas were 1.7 and 1.1, respectively. With advancing maternal age there was a smoking-related relative increase in the odds ratios for small-for-gestational-age births. Moreover, the age effect on the relative increase of low birth weight, preterm delivery, and small-for-gestational-age births was greater among nulliparas than multiparas. CONCLUSIONS Older smokers are at an especially high risk for small-for-gestational-age births, and parous smokers are at an especially high risk for low birth weight and preterm delivery.

High adiposity and high body mass index–for-age in US children and adolescents overall and by race-ethnic group

BACKGROUND Body mass index (BMI)-for-age has been recommended as a screening test for excess adiposity in children and adolescents. OBJECTIVE We quantified the performance of standard categories of BMI-for-age relative to the population prevalence of high adiposity in children and adolescents overall and by race-ethnic group in a nationally representative US population sample by using definitions of high adiposity that are consistent with expert committee recommendations. DESIGN Percentage body fat in 8821 children and adolescents aged 8-19 y was measured by using dual-energy X-ray absorptiometry in 1999-2004 as part of a health examination survey. RESULTS With the use of several different cutoffs for percentage fat to define high adiposity, most children with high BMI-for-age (> or = 95th percentile of the growth charts) had high adiposity, and few children with normal BMI-for-age (<85th percentile) had high adiposity. The prevalence of high adiposity in intermediate BMI categories varied from 45% to 15% depending on the cutoff. The prevalence of a high BMI was significantly higher in non-Hispanic black girls than in non-Hispanic white girls, but the prevalence of high adiposity was not significantly different. CONCLUSIONS Current BMI cutoffs can identify a high prevalence of high adiposity in children with high BMI-for-age and a low prevalence of high adiposity in children with normal BMI-for-age. By these adiposity measures, less than one-half of children with intermediate BMIs-for-age (85th to <95th percentile) have high adiposity. Differences in high BMI ranges between race-ethnic groups do not necessarily indicate differences in high adiposity.