June Stevens

The Effect of Age on the Association between Body-Mass Index and Mortality

BACKGROUND The effect of age on optimal body weight is controversial, and few studies have had adequate numbers of subjects to analyze mortality as a function of body-mass index across age groups. METHODS We studied mortality over 12 years among white men and women who participated in the American Cancer Societys Cancer Prevention Study I (from 1960 through 1972). The 62,116 men and 262,019 women included in this analysis had never smoked cigarettes, had no history of heart disease, stroke, or cancer (other than skin cancer) at base line in 1959-1960, and had no history of recent unintentional weight loss. The date and cause of death for subjects who died were determined from death certificates. The associations between body-mass index (defined as the weight in kilograms divided by the square of the height in meters) and mortality were examined for six age groups in analyses in which we adjusted for age, educational level, physical activity, and alcohol consumption. RESULTS Greater body-mass index was associated with higher mortality from all causes and from cardiovascular disease in men and women up to 75 years of age. However, the relative risk associated with greater body-mass index declined with age. For example, for mortality from cardiovascular disease, the relative risk associated with an increment of 1 in the body-mass index was 1.10 (95 percent confidence interval, 1.04 to 1.16) for 30-to-44-year-old men and 1.03 (95 percent confidence interval, 1.02 to 1.05) for 65-to-74-year-old men. For women, the corresponding relative risk estimates were 1.08 (95 percent confidence interval, 1.05 to 1.11) and 1.02 (95 percent confidence interval, 1.02 to 1.03). CONCLUSIONS Excess body weight increases the risk of death from any cause and from cardiovascular disease in adults between 30 and 74 years of age. The relative risk associated with greater body weight is higher among younger subjects.

2013 AHA/ACC/TOS guideline for the management of overweight and obesity in adults: A report of the American College of cardiology/American Heart Association task force on practice guidelines and the obesity society

Harmon S. Jordan, ScD, Karima A. Kendall, PhD, Linda J. Lux, Roycelynn Mentor-Marcel, PhD, MPH, Laura C. Morgan, MA, Michael G. Trisolini, PhD, MBA, Janusz Wnek, PhD Jeffrey L. Anderson, MD, FACC, FAHA, Chair , Jonathan L. Halperin, MD, FACC, FAHA, Chair-Elect , Nancy M. Albert, PhD, CCNS, CCRN,Obesity is a chronic, multifactor disease with sizeable socio sanitary and economic consequences and is an issue in public health, mostly in developing countries. It causes or exacerbates a large number of health problems: diabetes, coronary heart disease, hypertension, and the incidence of certain cancers. It has been linked to a greater risk of cardiovascular mortality, a higher prevalence of psychopathology disorders and social maladjustment with a higher health care cost and shorter life-expectancy. In Spain, nowadays, the prevalence of overweight and obesity is nearly 50% of population. SEEN has developed a Clinical Practice Guide on diagnosis, evaluation and treatment of overweight and obesity in adult people with two sections: 1) Definition and classification of adult obesity, its epidemiology, etiopathogeny, complications, benefits of weight reduction and clinical evaluation of patients with overweight or obesity, and 2) Identification of patients with obesity risk subsidiary to weight reduction treatment, therapy goals and therapeutical strategies available to achieve them indicating as well the degree of recommendation based upon scientific evidence on each aspect. Although obesity is a disease which is supposed to involve not only medical but also political authorities, social agents, educators and food industry among others, SEEN decided to develop this Guide taking into account the evident endocrinological and metabolical aspects of this disorder. The Guide contains scientific evidencebased recommendations intended to help doctors making decisions on diagnose, evaluations and treatment of adult overweight so that a more homogeneous attendance with settled quality can be

2013 AHA/ACC/TOS Guideline for the Management of Overweight and Obesity in Adults

Loria, Barbara E. Millen, Cathy A. Nonas, F. Xavier Pi-Sunyer, June Stevens, Victor J. Stevens, Karen A. Donato, Frank B. Hu, Van S. Hubbard, John M. Jakicic, Robert F. Kushner, Catherine M. Michael D. Jensen, Donna H. Ryan, Caroline M. Apovian, Jamy D. Ard, Anthony G. Comuzzie, Practice Guidelines and The Obesity Society Report of the American College of Cardiology/American Heart Association Task Force on 2013 AHA/ACC/TOS Guideline for the Management of Overweight and Obesity in Adults: A Print ISSN: 0009-7322. Online ISSN: 1524-4539 Copyright

Dietary Intake and the Development of the Metabolic Syndrome The Atherosclerosis Risk in Communities Study

Background— The role of diet in the origin of metabolic syndrome (MetSyn) is not well understood; thus, we sought to evaluate the relationship between incident MetSyn and dietary intake using prospective data from 9514 participants (age, 45 to 64 years) enrolled in the Atherosclerosis Risk in Communities (ARIC) study. Methods and Results— Dietary intake was assessed at baseline via a 66-item food frequency questionnaire. We used principal-components analysis to derive “Western” and “prudent” dietary patterns from 32 food groups and evaluated 10 food groups used in previous studies of the ARIC cohort. MetSyn was defined by American Heart Association guidelines. Proportional-hazards regression was used. Over 9 years of follow-up, 3782 incident cases of MetSyn were identified. After adjustment for demographic factors, smoking, physical activity, and energy intake, consumption of a Western dietary pattern (Ptrend=0.03) was adversely associated with incident MetSyn. After further adjustment for intake of meat, dairy, fruits and vegetables, refined grains, and whole grains, analysis of individual food groups revealed that meat (Ptrend<0.001), fried foods (Ptrend=0.02), and diet soda (Ptrend=< 0.001) also were adversely associated with incident MetSyn, whereas dairy consumption (Ptrend=0.006) was beneficial. No associations were observed between incident MetSyn and a prudent dietary pattern or intakes of whole grains, refined grains, fruits and vegetables, nuts, coffee, or sweetened beverages. Conclusions— These prospective findings suggest that consumption of a Western dietary pattern, meat, and fried foods promotes the incidence of MetSyn, whereas dairy consumption provides some protection. The diet soda association was not hypothesized and deserves further study.

Separate and combined associations of body-mass index and abdominal adiposity with cardiovascular disease : collaborative analysis of 58 prospective studies

BACKGROUND Guidelines differ about the value of assessment of adiposity measures for cardiovascular disease risk prediction when information is available for other risk factors. We studied the separate and combined associations of body-mass index (BMI), waist circumference, and waist-to-hip ratio with risk of first-onset cardiovascular disease. METHODS We used individual records from 58 cohorts to calculate hazard ratios (HRs) per 1 SD higher baseline values (4.56 kg/m(2) higher BMI, 12.6 cm higher waist circumference, and 0.083 higher waist-to-hip ratio) and measures of risk discrimination and reclassification. Serial adiposity assessments were used to calculate regression dilution ratios. RESULTS Individual records were available for 221,934 people in 17 countries (14,297 incident cardiovascular disease outcomes; 1.87 million person-years at risk). Serial adiposity assessments were made in up to 63,821 people (mean interval 5.7 years [SD 3.9]). In people with BMI of 20 kg/m(2) or higher, HRs for cardiovascular disease were 1.23 (95% CI 1.17-1.29) with BMI, 1.27 (1.20-1.33) with waist circumference, and 1.25 (1.19-1.31) with waist-to-hip ratio, after adjustment for age, sex, and smoking status. After further adjustment for baseline systolic blood pressure, history of diabetes, and total and HDL cholesterol, corresponding HRs were 1.07 (1.03-1.11) with BMI, 1.10 (1.05-1.14) with waist circumference, and 1.12 (1.08-1.15) with waist-to-hip ratio. Addition of information on BMI, waist circumference, or waist-to-hip ratio to a cardiovascular disease risk prediction model containing conventional risk factors did not importantly improve risk discrimination (C-index changes of -0.0001, -0.0001, and 0.0008, respectively), nor classification of participants to categories of predicted 10-year risk (net reclassification improvement -0.19%, -0.05%, and -0.05%, respectively). Findings were similar when adiposity measures were considered in combination. Reproducibility was greater for BMI (regression dilution ratio 0.95, 95% CI 0.93-0.97) than for waist circumference (0.86, 0.83-0.89) or waist-to-hip ratio (0.63, 0.57-0.70). INTERPRETATION BMI, waist circumference, and waist-to-hip ratio, whether assessed singly or in combination, do not importantly improve cardiovascular disease risk prediction in people in developed countries when additional information is available for systolic blood pressure, history of diabetes, and lipids. FUNDING British Heart Foundation and UK Medical Research Council.Summary Background Guidelines differ about the value of assessment of adiposity measures for cardiovascular disease risk prediction when information is available for other risk factors. We studied the separate and combined associations of body-mass index (BMI), waist circumference, and waist-to-hip ratio with risk of first-onset cardiovascular disease. Methods We used individual records from 58 cohorts to calculate hazard ratios (HRs) per 1 SD higher baseline values (4·56 kg/m2 higher BMI, 12·6 cm higher waist circumference, and 0·083 higher waist-to-hip ratio) and measures of risk discrimination and reclassification. Serial adiposity assessments were used to calculate regression dilution ratios. Results Individual records were available for 221 934 people in 17 countries (14 297 incident cardiovascular disease outcomes; 1·87 million person-years at risk). Serial adiposity assessments were made in up to 63 821 people (mean interval 5·7 years [SD 3·9]). In people with BMI of 20 kg/m2 or higher, HRs for cardiovascular disease were 1·23 (95% CI 1·17–1·29) with BMI, 1·27 (1·20–1·33) with waist circumference, and 1·25 (1·19–1·31) with waist-to-hip ratio, after adjustment for age, sex, and smoking status. After further adjustment for baseline systolic blood pressure, history of diabetes, and total and HDL cholesterol, corresponding HRs were 1·07 (1·03–1·11) with BMI, 1·10 (1·05–1·14) with waist circumference, and 1·12 (1·08–1·15) with waist-to-hip ratio. Addition of information on BMI, waist circumference, or waist-to-hip ratio to a cardiovascular disease risk prediction model containing conventional risk factors did not importantly improve risk discrimination (C-index changes of −0·0001, −0·0001, and 0·0008, respectively), nor classification of participants to categories of predicted 10-year risk (net reclassification improvement −0·19%, −0·05%, and −0·05%, respectively). Findings were similar when adiposity measures were considered in combination. Reproducibility was greater for BMI (regression dilution ratio 0·95, 95% CI 0·93–0·97) than for waist circumference (0·86, 0·83–0·89) or waist-to-hip ratio (0·63, 0·57–0·70). Interpretation BMI, waist circumference, and waist-to-hip ratio, whether assessed singly or in combination, do not importantly improve cardiovascular disease risk prediction in people in developed countries when additional information is available for systolic blood pressure, history of diabetes, and lipids. Funding British Heart Foundation and UK Medical Research Council.

Separate and combined associations of body-mass index and abdominal adiposity with cardiovascular disease: collaborative analysis of 58 prospective studies

BACKGROUND Guidelines differ about the value of assessment of adiposity measures for cardiovascular disease risk prediction when information is available for other risk factors. We studied the separate and combined associations of body-mass index (BMI), waist circumference, and waist-to-hip ratio with risk of first-onset cardiovascular disease. METHODS We used individual records from 58 cohorts to calculate hazard ratios (HRs) per 1 SD higher baseline values (4.56 kg/m(2) higher BMI, 12.6 cm higher waist circumference, and 0.083 higher waist-to-hip ratio) and measures of risk discrimination and reclassification. Serial adiposity assessments were used to calculate regression dilution ratios. RESULTS Individual records were available for 221,934 people in 17 countries (14,297 incident cardiovascular disease outcomes; 1.87 million person-years at risk). Serial adiposity assessments were made in up to 63,821 people (mean interval 5.7 years [SD 3.9]). In people with BMI of 20 kg/m(2) or higher, HRs for cardiovascular disease were 1.23 (95% CI 1.17-1.29) with BMI, 1.27 (1.20-1.33) with waist circumference, and 1.25 (1.19-1.31) with waist-to-hip ratio, after adjustment for age, sex, and smoking status. After further adjustment for baseline systolic blood pressure, history of diabetes, and total and HDL cholesterol, corresponding HRs were 1.07 (1.03-1.11) with BMI, 1.10 (1.05-1.14) with waist circumference, and 1.12 (1.08-1.15) with waist-to-hip ratio. Addition of information on BMI, waist circumference, or waist-to-hip ratio to a cardiovascular disease risk prediction model containing conventional risk factors did not importantly improve risk discrimination (C-index changes of -0.0001, -0.0001, and 0.0008, respectively), nor classification of participants to categories of predicted 10-year risk (net reclassification improvement -0.19%, -0.05%, and -0.05%, respectively). Findings were similar when adiposity measures were considered in combination. Reproducibility was greater for BMI (regression dilution ratio 0.95, 95% CI 0.93-0.97) than for waist circumference (0.86, 0.83-0.89) or waist-to-hip ratio (0.63, 0.57-0.70). INTERPRETATION BMI, waist circumference, and waist-to-hip ratio, whether assessed singly or in combination, do not importantly improve cardiovascular disease risk prediction in people in developed countries when additional information is available for systolic blood pressure, history of diabetes, and lipids. FUNDING British Heart Foundation and UK Medical Research Council.Summary Background Guidelines differ about the value of assessment of adiposity measures for cardiovascular disease risk prediction when information is available for other risk factors. We studied the separate and combined associations of body-mass index (BMI), waist circumference, and waist-to-hip ratio with risk of first-onset cardiovascular disease. Methods We used individual records from 58 cohorts to calculate hazard ratios (HRs) per 1 SD higher baseline values (4·56 kg/m2 higher BMI, 12·6 cm higher waist circumference, and 0·083 higher waist-to-hip ratio) and measures of risk discrimination and reclassification. Serial adiposity assessments were used to calculate regression dilution ratios. Results Individual records were available for 221 934 people in 17 countries (14 297 incident cardiovascular disease outcomes; 1·87 million person-years at risk). Serial adiposity assessments were made in up to 63 821 people (mean interval 5·7 years [SD 3·9]). In people with BMI of 20 kg/m2 or higher, HRs for cardiovascular disease were 1·23 (95% CI 1·17–1·29) with BMI, 1·27 (1·20–1·33) with waist circumference, and 1·25 (1·19–1·31) with waist-to-hip ratio, after adjustment for age, sex, and smoking status. After further adjustment for baseline systolic blood pressure, history of diabetes, and total and HDL cholesterol, corresponding HRs were 1·07 (1·03–1·11) with BMI, 1·10 (1·05–1·14) with waist circumference, and 1·12 (1·08–1·15) with waist-to-hip ratio. Addition of information on BMI, waist circumference, or waist-to-hip ratio to a cardiovascular disease risk prediction model containing conventional risk factors did not importantly improve risk discrimination (C-index changes of −0·0001, −0·0001, and 0·0008, respectively), nor classification of participants to categories of predicted 10-year risk (net reclassification improvement −0·19%, −0·05%, and −0·05%, respectively). Findings were similar when adiposity measures were considered in combination. Reproducibility was greater for BMI (regression dilution ratio 0·95, 95% CI 0·93–0·97) than for waist circumference (0·86, 0·83–0·89) or waist-to-hip ratio (0·63, 0·57–0·70). Interpretation BMI, waist circumference, and waist-to-hip ratio, whether assessed singly or in combination, do not importantly improve cardiovascular disease risk prediction in people in developed countries when additional information is available for systolic blood pressure, history of diabetes, and lipids. Funding British Heart Foundation and UK Medical Research Council.

Body-mass index and all-cause mortality: Individual-participant-data meta-analysis of 239 prospective studies in four continents.

Summary Background Overweight and obesity are increasing worldwide. To help assess their relevance to mortality in different populations we conducted individual-participant data meta-analyses of prospective studies of body-mass index (BMI), limiting confounding and reverse causality by restricting analyses to never-smokers and excluding pre-existing disease and the first 5 years of follow-up. Methods Of 10 625 411 participants in Asia, Australia and New Zealand, Europe, and North America from 239 prospective studies (median follow-up 13·7 years, IQR 11·4–14·7), 3 951 455 people in 189 studies were never-smokers without chronic diseases at recruitment who survived 5 years, of whom 385 879 died. The primary analyses are of these deaths, and study, age, and sex adjusted hazard ratios (HRs), relative to BMI 22·5–<25·0 kg/m2. Findings All-cause mortality was minimal at 20·0–25·0 kg/m2 (HR 1·00, 95% CI 0·98–1·02 for BMI 20·0–<22·5 kg/m2; 1·00, 0·99–1·01 for BMI 22·5–<25·0 kg/m2), and increased significantly both just below this range (1·13, 1·09–1·17 for BMI 18·5–<20·0 kg/m2; 1·51, 1·43–1·59 for BMI 15·0–<18·5) and throughout the overweight range (1·07, 1·07–1·08 for BMI 25·0–<27·5 kg/m2; 1·20, 1·18–1·22 for BMI 27·5–<30·0 kg/m2). The HR for obesity grade 1 (BMI 30·0–<35·0 kg/m2) was 1·45, 95% CI 1·41–1·48; the HR for obesity grade 2 (35·0–<40·0 kg/m2) was 1·94, 1·87–2·01; and the HR for obesity grade 3 (40·0–<60·0 kg/m2) was 2·76, 2·60–2·92. For BMI over 25·0 kg/m2, mortality increased approximately log-linearly with BMI; the HR per 5 kg/m2 units higher BMI was 1·39 (1·34–1·43) in Europe, 1·29 (1·26–1·32) in North America, 1·39 (1·34–1·44) in east Asia, and 1·31 (1·27–1·35) in Australia and New Zealand. This HR per 5 kg/m2 units higher BMI (for BMI over 25 kg/m2) was greater in younger than older people (1·52, 95% CI 1·47–1·56, for BMI measured at 35–49 years vs 1·21, 1·17–1·25, for BMI measured at 70–89 years; pheterogeneity<0·0001), greater in men than women (1·51, 1·46–1·56, vs 1·30, 1·26–1·33; pheterogeneity<0·0001), but similar in studies with self-reported and measured BMI. Interpretation The associations of both overweight and obesity with higher all-cause mortality were broadly consistent in four continents. This finding supports strategies to combat the entire spectrum of excess adiposity in many populations. Funding UK Medical Research Council, British Heart Foundation, National Institute for Health Research, US National Institutes of Health.

The definition of weight maintenance

There is currently no consensus on the definition of weight maintenance in adults. Issues to consider in setting a standard definition include expert opinion, precedents set in previous studies, public health and clinical applications, comparability across body sizes, measurement error, normal weight fluctuations and biologic relevance. To be useful, this definition should indicate an amount of change less than is clinically relevant, but more than expected from measurement error or fluctuations in fluid balance under normal conditions. It is an advantage for the definition to be graded by body size and to be easily understood by the public as well as scientists. Taking all these factors into consideration, the authors recommend that long-term weight maintenance in adults be defined as a weight change of <3% of body weight.

Promoting Physical Activity in Middle School Girls Trial of Activity for Adolescent Girls

BACKGROUND Physical activity is important for weight control and good health; however, activity levels decline in the adolescent years, particularly in girls. DESIGN Group randomized controlled trial. SETTING/PARTICIPANTS Middle school girls with English-speaking skills and no conditions to prevent participation in physical activity in 36 schools in six geographically diverse areas of the United States. Random, cross-sectional samples were drawn within schools: 6th graders in 2003 (n=1721) and 8th graders in 2005 (n=3504) and 2006 (n=3502). INTERVENTION A 2-year study-directed intervention (fall 2003 to spring 2005) targeted schools, community agencies, and girls to increase opportunities, support, and incentives for increased physical activity. Components included programs linking schools and community agencies, physical education, health education, and social marketing. A third-year intervention used school and community personnel to direct intervention activities. MAIN OUTCOME MEASURES The primary outcome, daily MET-weighted minutes of moderate-to-vigorous physical activity (MET-weighted MVPA), was assessed using accelerometry. Percent body fat was assessed using anthropometry. RESULTS After the staff-directed intervention (pre-stated primary outcome), there were no differences (mean= -0.4, 95% CI= -8.2 to 7.4) in adjusted MET-weighted MVPA between 8th-grade girls in schools assigned to intervention or control. Following the Program Champion-directed intervention, girls in intervention schools were more physically active than girls in control schools (mean difference 10.9 MET-weighted minutes of MVPA, 95% CI=0.52-21.2). This difference is about 1.6 minutes of daily MVPA or 80 kcal per week. There were no differences in fitness or percent body fat at either 8th-grade timepoint. CONCLUSION A school-based, community-linked intervention modestly improved physical activity in girls.

A Prospective Study of Coronary Heart Disease in Relation to Fasting Insulin, Glucose, and Diabetes: The Atherosclerosis Risk in Communities (ARIC) Study

OBJECTIVE To determine the association of coronary heart disease (CHD) incidence with diabetes, fasting serum glucose, and insulin in a biracial cohort of middle-aged men and women. RESEARCH DESIGN AND METHODS We examined a population-based sample (n = 13,446 free of baseline CHD) from four U.S. communities in 1987–1989. We defined diabetes on the basis of baseline fasting glucose concentration (≥ 7.8 mmol/l), medical history, and current medications. A central laboratory measured fasting insulin with a nonspecific radioimmunoassay. After 4–7 years, 209 men and 96 women developed CHD. RESULTS After adjustment for sociodemographic characteristics, smoking status, ethanol intake, sports participation, and hormone replacement therapy, the relative risk of CHD for people with diabetes versus those without diabetes was 3.45 (95% CI 2.16–5.50) among women and 2.52 (1.78–3.56) among men. Relative risks of CHD with diabetes were somewhat lower in blacks than non-blacks, but because diabetes was more than twice as prevalent in blacks, the percentage of CHD cases attributable to diabetes (population attributable risk) was 27% for black women, 15% for non-black women, 8% for black men, and 12% for non-black men. Among people without diabetes, fasting glucose was not independently associated with CHD incidence. Among women without diabetes, there was a positive association between fasting insulin and CHD; multivariable adjusted relative risks of CHD across quintiles of fasting insulin were 1.00, 0.76, 2.08, 2.08 and 2.82 (P for linear trend = 0.02). However, among men without diabetes, fasting insulin and CHD were not associated. CONCLUSIONS Diabetes conveys a high risk of CHD in black and non-black middle-aged men and women. Fasting insulin, however, is a CHD risk factor only among women in this cohort.