Overweight and obesity as determinants of cardiovascular risk: the Framingham experience. Obesity and Mortality in a Prospective Study of a Middle-Aged Industrial Population Reverse causality and confounding and the associations of overweight and obesity with mortality. The effects of physical activity and body mass index on cardiovascular, cancer and all-cause mortality among 47 212 middle-aged Finnish men and women A prospective study of obesity and risk of coronary heart disease in women. The epidemic of obesity and diabetes: trends and treatments. Overweight, obesity, and mortality from cancer in a prospectively studied cohort of U.S. adults. Overweight, underweight, and mortality. A prospective study of 48,287 men and women. The Natural History of the Development of Obesity in a Cohort of Young U.S. Adults between 1981 and 1998 The association of body mass index with the risk of type 2 diabetes: a case–control study nested in an electronic health records system in the United States Overweight, obesity, and mortality in a large prospective cohort of persons 50 to 71 years old. International Day for the Evaluation of Abdominal Obesity (IDEA): A Study of Waist Circumference, Cardiovascular Disease, and Diabetes Mellitus in 168 000 Primary Care Patients in 63 Countries Influence of obesity on outcomes in atrial fibrillation: yet another obesity paradox. Overweight and obesity and weight change in middle aged men: impact on cardiovascular disease and diabetes Obesity paradox in patients with hypertension and coronary artery disease. Obesity and outcomes among patients with established atrial fibrillation. Body mass index and adverse events in patients with incident atrial fibrillation.
BACKGROUND To our knowledge , no single investigation concerning the long-term effects of overweight status on the risk for hypertension , hypercholesterolemia , diabetes mellitus , and cardiovascular sequelae has been reported . METHODS Relations between categories of body mass index ( BMI ) , cardiovascular disease risk factors , and vascular disease end points were examined prospect ively in Framingham Heart Study participants aged 35 to 75 years , who were followed up to 44 years . The primary outcome was new cardiovascular disease , which included angina pectoris , myocardial infa rct ion , coronary heart disease , or stroke . Analyses compared  overweight ( BMI [ calculated as weight in kilograms divided by the square of height in meters ] , 25.0 - 29.9 ) and obese persons ( BMI > or = 30 )  to a  referent group of normal-weight persons ( BMI , 18.5 - 24.9 ) . RESULTS The age-adjusted relative risk ( RR ) for new hypertension was highly associated with overweight status ( men : RR , 1.46 ; women : RR , 1.75 ) . New hypercholesterolemia and diabetes mellitus were less highly associated with excess adiposity . The age-adjusted RR ( confidence interval [ CI ] ) for cardiovascular disease was increased among those who were overweight ( men : 1.21 [ 1.05 - 1.40 ] ; women : 1.20 [ 1.03 - 1.41 ] ) and the obese ( men : 1.46 [ 1.20 - 1.77 ] ; women : 1.64 [ 1.37 - 1.98 ] ) . High population attributable risks were related to excess weight ( BMI > or = 25 ) for the outcomes hypertension ( 26 % men ; 28 % women ) , angina pectoris ( 26 % men ; 22 % women ) , and coronary heart disease ( 23 % men ; 15 % women ) . CONCLUSIONS The overweight category is associated with increased relative and population attributable risk for hypertension and cardiovascular sequelae . Interventions to reduce adiposity and avoid excess weight may have large effects on the development of risk factors and cardiovascular disease at an individual and population level Background : Although obesity is an established risk factor for coronary heart disease and stroke mortality , its role as a risk factor for other causes of death has not been extensively investigated , particularly in an industrial population . Methods : This prospect i ve mortality study included 20 years of follow up of middle-aged industrial workers ( n = 7139 ) at Shell Oil Company 's manufacturing and research facilities . Baseline health risk factor data as of December 31 , 1983 , and mortality data as of December 31 , 2003 , were extracted from the company 's Health Surveillance System . Relative risks ( RRs ) for selected causes of death by body mass index ( BMI ) category were calculated using the Cox proportional hazards model adjusted for age , sex , and smoking status as well as other potential risk factors , ie , cholesterol , hypertension , and fasting blood glucose . Results : Compared with employees with BMI between 18.5 and 24.9 kg/m2 , those with BMI of 30 kg/m2 or greater had a statistically increased RR ( adjusted for age , sex , and smoking status ) for all causes ( RR , 1.25 ; 95 % confidence interval [ CI ] = 1.03–1.51 ) , coronary heart diseases ( RR , 2.29 ; 95 % CI = 1.50–3.50 ) , cardiovascular diseases ( RR , 2.22 ; 95 % CI = 1.51–3.27 ) , diabetes ( RR , 16.97 ; 95 % CI = 2.11–136.44 ) , and accidental deaths ( RR , 2.64 ; 95 % CI = 1.23–5.66 ) . After adjusting for additional covariates , coronary heart diseases and cardiovascular diseases remained statistically significant . Conclusions : Obesity was associated with increased death rates for all causes , cardiovascular diseases , diabetes , and all accidents . Overweight individuals had a statistically lower cancer rate . Death rates for lung cancer and respiratory disease were lower among overweight/obese employees but did not reach statistical significance . Reductions of employee obesity can be an effective means of reducing these causes of death OBJECTIVE To examine the effect of reverse causality and confounding on the association of BMI with all-cause and cause-specific mortality . RESEARCH METHODS AND PROCEDURES Data from two large prospect i ve studies were used . One ( a community-based cohort ) included 8327 women and 7017 men who resided in two Scottish towns at the time of the baseline assessment in 1972 - 1976 ; the other ( an occupational cohort ) included 4016 men working in the central belt of Scotl and at the time of the baseline assessment in 1970 - 1973 . Participants in both cohorts were ages 45 to 64 years at baseline ; the follow-up period was 28 to 34 years . RESULTS In age-adjusted analyses that did not take account of reverse causality or smoking , there was no association between being overweight ( BMI 25 to < 30 kg/m(2 ) ) and mortality , and weak to modest associations between obesity ( BMI > or = 30 kg/m(2 ) ) and mortality . There was a strong association between smoking and lower BMI in women and men in both cohorts ( all p < 0.0001 ) . Among never-smokers and with the first 5 years of deaths removed , overweight was associated with an increase in all-cause mortality ( relative risk ranging from 1.12 to 1.38 ) , and obesity was associated with a doubling of risk in men in both cohorts ( relative risk , 2.10 and 1.96 , respectively ) and a 60 % increase in women ( relative risk , 1.56 ) . In both never-smokers and current smokers , being overweight or obese was associated with important increases in the risk of cardiovascular disease . DISCUSSION These findings demonstrate that with appropriate control for smoking and reverse causality , both overweight and obesity are associated with important increases in all-cause and cause-specific mortality , and in particular with cardiovascular disease mortality OBJECTIVE : To examine the association of physical activity and body mass index ( BMI ) , and their combined effect , with the risk of total , cardiovascular disease ( CVD ) and cancer mortality .  DESIGN : Prospect i ve follow-up study .SUBJECTS : In all , 22 528 men and 24 684 women aged 25–64 y at baseline having 7394 deaths during a mean follow-up of 17.7 y . MEASUREMENT : A self-administered question naire data on smoking , socioeconomic factors , physical activity and medical history , together with measured height , weight , blood pressure and serum cholesterol using st and ardized protocol . RESULT : Physically active subjects had significantly lower age-adjusted mortality from cardiovascular , cancer and all causes compared with sedentary ones . Further adjustment for smoking , systolic blood pressure , cholesterol , BMI , diabetes and education affected the results only slightly . Obese subjects ( BMI ≥30 kg/m2 ) had significantly higher cardiovascular and total mortality than the normal weight ( 18.5≤ BMI < 25 kg/m2 ) subjects . Part of increased mortality among obese subjects was mediated through obesity-related cardiovascular risk factors . BMI had an inverse association with cancer mortality among men and almost significant direct association among women . Total mortality was also increased among the lean ( BMI < 18.5 kg/m2 ) subjects . However , less than 0.3 % of deaths were attributed to low body weight , whereas in men 5.5 % and in women 17.7 % of deaths were attributed to obesity . CONCLUSION : Regular physical activity and normal weight are both important indicators for a decreased risk of mortality from all causes , CVD and cancer . Physical activity had a strong independent effect on mortality , whereas the effect of BMI was partly mediated through other obesity-related risk factors We examined the incidence of  nonfatal and fatal coronary heart disease in relation to obesity in a prospect i ve cohort study of 115,886 U.S. women who were 30 to 55 years of age in 1976 and free of diagnosed coronary disease , stroke , and cancer . During eight years of follow-up ( 775,430 person-years ) , we identified 605 first coronary events , including 306 nonfatal myocardial infa rct ions , 83 deaths due to coronary heart disease , and 216 cases of confirmed angina pectoris . A higher Quetelet index ( weight in kilograms divided by the square of the height in meters ) was positively associated with the occurrence of each category of coronary heart disease . For increasing levels of current Quetelet index ( less than 21 , 21 to less than 23 , 23 to less than 25 , 25 to less than 29 , and greater than or equal to 29 ) , the relative risks of nonfatal myocardial infa rct ion and fatal coronary heart disease combined , as adjusted for age and cigarette smoking , were 1.0 , 1.3 , 1.3 , 1.8 , and 3.3 ( Mantel-extension chi for trend = 7.29 ; P less than 0.00001 ) . As expected , control for a history of hypertension , diabetes mellitus , and hypercholesterolemia -- conditions known to be biologic effects of obesity -- attenuated the strength of the association . The current Quetelet index was a more important determinant of coronary risk than that at the age of 18 ; an intervening weight gain increased risk substantially . These prospect i ve data emphasize the importance of obesity as a determinant of coronary heart disease in women . After control for cigarette smoking , which is essential to assess the true effects of obesity , even mild-to-moderate overweight increased the risk of coronary disease in middle-aged women Cardiovascular disease remains the leading cause of death in women . Both obesity and diabetes mellitus are important independent risk factors for the development of cardiovascular disease . Obesity is the leading risk factor for type 2 diabetes . The Centers for Disease Control and Prevention report that 32 % of white and 53 % of black women are obese . Women with a body mass index ( BMI ) of 30 kg/m2 have a 28 times greater risk of developing diabetes than do women of normal weight . The risk of diabetes is 93 times greater if the BMI is 35 kg/m2.1 The presence of diabetes can increase a woman 's risk of heart disease 2-fold . In addition , the presence of diabetes overshadows the protective effects of the premenopausal state . In 2007 , 11.5 million of all women over the age of 20 ( 10.2 % ) had diabetes , and rates were slightly higher in ethnic minority groups : 10.4 % in Hispanic women and 11.8 % in non-Hispanic black women.2 The national prevalence rates of diabetes have increased in parallel with the rates of obesity ( Fig. 1 ) . Fig. 1 Age-adjusted percentage of U.S. adults who were obese or who had a diagnosis of diabetes mellitus . Screening Screening for obesity and diabetes is the 1st step to treatment and often reveals individuals who are at risk for but do not yet have overt disease . The United States Preventive Services Task Force ( USPSTF ) recommends that all adults be screened for obesity . Obesity signifies excess adipose tissue . The most widely used method for screening is determination of the BMI . The BMI is weight in kilograms divided by height in meters squared ( BMI = kg/m2 ) ( Table I ) . Most electronic medical records automatically calculate BMI if height and weight are entered . There are also many smart-phone applications and online calculators that can calculate BMI ( for example , http://www.nhlbisupport.com/ bmi ) . Other screening tools include  waist circumference and the waist-to-hip ratio . In women , a waist circumference > 35 in ( 88 cm ) or a waist-to-hip ratio > 0.7 indicates excess visceral fat and increased risk for disease . TABLE I. Body Mass Index ( BMI ) Classification Recommendations for screening for diabetes vary by guideline author . The USPSTF recommends screening asymptomatic patients who have  blood pressures > 135/80 mmHg  . The American Diabetes Association ( ADA ) recommends that individuals who are ≥18 years of age and have a BMI ≥25 kg/m2 and 1 additional risk factor for diabetes should be screened annually ( Table II).3 Individuals over the age of 45 without risk factors should be screened every 3 years . In January 2010 , the ADA released new recommendations for the use of hemoglobin A1C as a screening tool . An A1C greater than 6.5 % indicates diabetes . In addition , the results of screening tests for diabetes can identify individuals with “ prediabetes ” who have a markedly increased risk of developing overt disease.3 TABLE II . American Diabetes Association Recommendations on Screening for Type 2 Diabetes3 Non-Pharmaceutical Treatment Lifestyle-treatment options for diabetes mellitus and excess weight are similar , and 2 recent studies 4,5 have demonstrated the critical components for treating pre-diabetes and diabetes through weight loss , using caloric restriction and physical activity . The 1st study was the Diabetes Prevention Program.4 The purpose of the study was to identify individuals who were at risk for developing diabetes because of elevated fasting plasma glucose or impaired glucose tolerance levels that were not yet in the diagnostic range , in order to determine if metformin or an intensive lifestyle intervention could delay or prevent the onset of diabetes . More than 3,000 individuals with prediabetes were r and omized to receive placebo , metformin , or a 16-session lifestyle-modification program . The intensive lifestyle program set a goal of 7 % weight loss and 150 min/wk of moderate physical activity . Fifty percent of the lifestyle-intervention group lost 7 % of their body weight . The 3-year incidence of diabetes in the metformin group was 31 % lower than that in the placebo group . The incidence was 58 % lower in the lifestyle group than in the placebo group.4 The clinical implication s of this study are that we should 1 ) identify individuals with pre-diabetes and 2 ) recommend lifestyle modifications that result in a 7 % weight loss and include 150 min/wk of moderate physical activity . The 2nd study that examined lifestyle treatment of diabetes and obesity is the Look AHEAD Trial . The purpose of the study was to determine the effect of intentional weight loss on cardiovascular risk factors in individuals with diabetes . Approximately 5,100 individuals with type 2 diabetes and an elevated BMI were r and omized . Study conditions specified a 36-session intensive lifestyle intervention with the option of using partial meal replacements for caloric restriction or 4 sessions of st and ard diabetes support and education ( DSE ) . At 1 year , 55 % of the intensive-lifestyle-intervention group achieved 7 % weight loss . Hemoglobin A1C , systolic and diastolic blood pressure , and lipids improved significantly more in the intensive-lifestyle group than in the DSE group.5 The clinical implication of this study is that intentional weight loss of at least 7 % can improve the cardiovascular risk profile of patients with type 2 diabetes . Conclusions Excess weight affects two thirds of the U.S. adult population and increases risk for cardiovascular disease and diabetes . All patients should be screened for obesity and most should be screened for pre-diabetes and diabetes . The best treatment for diabetes is prevention . Prevention of diabetes can be accomplished through a 7 % weight loss through intensive lifestyle interventions that include caloric reduction and approximately 30 min of daily moderate physical activity . Practitioners will have access to these evidence -based programs soon . The Centers for Disease Control and Prevention are promoting community-based diabetes prevention programs throughout the country BACKGROUND The influence of excess body weight on the risk of death from  cancer  has not been fully characterized . METHODS In a prospect ively studied population of more than 900,000 U.S. adults ( 404,576 men and 495,477 women ) who were free of cancer at enrollment in 1982 , there were 57,145 deaths from cancer during 16 years of follow-up . We examined the relation in men and women between the body-mass index in 1982 and the risk of death from all cancers and from cancers at individual sites , while controlling for other risk factors in multivariate proportional-hazards models . We calculated the proportion of all deaths from cancer that was attributable to overweight and obesity in the U.S. population on the basis of risk estimates from the current study and national estimates of the prevalence of overweight and obesity in the U.S. adult population . RESULTS The heaviest members of this cohort ( those with a body-mass index [ the weight in kilograms divided by the square of the height in meters ] of at least 40 ) had death rates from all cancers combined that were 52 percent higher ( for men ) and 62 percent higher ( for women ) than the rates in men and women of normal weight . For men , the relative risk of death was 1.52 ( 95 percent confidence interval , 1.13 to 2.05 ) ; for women , the relative risk was 1.62 ( 95 percent confidence interval , 1.40 to 1.87 ) . In both men and women , body-mass index was also significantly associated with higher rates of death due to cancer of the esophagus , colon and rectum , liver , gallbladder , pancreas , and kidney ; the same was true for death due to non-Hodgkin 's lymphoma and multiple myeloma . Significant trends of increasing risk with higher body-mass-index values were observed for death from cancers of the stomach and prostate in men and for death from cancers of the breast , uterus , cervix , and ovary in women . On the basis of associations observed in this study , we estimate that current patterns of overweight and obesity in the United States could account for 14 percent of all deaths from cancer in men and 20 percent of those in women . CONCLUSIONS Increased body weight was associated with increased death rates for all cancers combined and for cancers at multiple specific sites BACKGROUND The relative contributions of a low and high body mass index ( BMI [ weight in kilograms divided by height in meters squared ] ) to all-cause and cause-specific mortality are still controversial . OBJECTIVE To examine mortality rates in relation to BMI in a prospect i ve cohort study of 48,287 Dutch men and women aged 30 to 54 years at baseline from 1974 to 1980 . METHODS During an average 12-year follow-up , 1319 deaths occurred . Relative risks ( RRs ) were calculated from the Cox proportional hazard model by using a BMI between 18.5 and 24.9 kg/m2 as the reference category . RESULTS All-cause mortality was significantly increased in obese men ( BMI , > or = 30 kg/m2 ; RR , 1.5 ; 95 % confidence interval [ CI ] , 1.1 - 2.0 ) and in underweight men ( BMI , < 18.5 kg/m2 ; RR , 2.6 ; 95 % CI , 1.8 - 3.9 ) but not in women . The increased risk in underweight men could be attributed to deaths within the first 5 years of follow-up and to lung cancer mortality among smokers . Coronary heart disease ( CHD ) mortality was about 3-fold higher among obese men and women . About 21 % and 28 % of CHD mortality in men and women , respectively , could be attributed to being overweight ( BMI , > or = 25 kg/m2 ) . The RR ( but not the absolute risk ) for CHD among obese men was still significant after adjustment for the presence of smoking , hypertension , hypercholesterolemia , and diabetes mellitus at baseline , and it was more pronounced for CHD among nonsmokers than among smokers ( RR , 7.1 ; 95 % CI , 2.3 - 21.7 ; and RR , 2.7 ; 95 % CI , 1.5 - 4.7 , respectively ) . CONCLUSIONS Total mortality was increased in obese and underweight men but not in women . The increased mortality in overweight men was mainly attributable to CHD and , in underweight men , to early mortality and especially lung cancer mortality among smokers Context Studies of the natural history of obesity have had limitations , such as cross-sectional design , short follow-up , or narrowly defined population s. Contribution Using data from a national study of Americans born between 1957 and 1964 and followed for nearly two decades , these investigators found that more than 25 % were obese by age 35 years . Obesity developed most quickly in black women , with moderate rapidity in Hispanic women , and most slowly in white women . Hispanic men developed obesity more quickly than other men . More recent birth cohorts became obese faster than earlier cohorts . Implication s Underst and ing ethnic differences in the age of onset and rate of progression of obesity may help efforts to prevent obesity . The Editors The proportion of Americans who are overweight or obese is increasing at an alarming rate . From 1960 to 1999 , the prevalence of excess weight ( body mass index [ BMI ] 25 kg/m2 ) increased from 44 % to 61 % of the adult population ( persons aged 20 to 74 years ) and the prevalence of obesity ( BMI 30 kg/m2 ) doubled from 13 % to 27 % ( 1 , 2 ) . Obesity has been linked to increased mortality and chronic morbidity from such diverse causes as hypertension , diabetes , sleep apnea , certain types of cancer , and depression . In the context of this rising prevalence , obesity is increasingly being recognized as an important medical and public health problem ( 3 - 6 ) . Treatment options are available for obesity . However , they can be expensive , often involve difficult lifestyle modifications , and pose adherence problems for many patients . In addition , weight loss , once achieved , is difficult to sustain . Because the health consequences are often long term , the costbenefit ratio of treatment may be more favorable if people who have recently become obese are targeted . Similarly , prevention should focus on those at immediate risk for becoming obese or overweight . Such approaches require a clear underst and ing of who is at highest risk for obesity , when this risk is greatest , and how excess weight develops over time . Although inactivity and high caloric intake are the primary risk factors for obesity , other risk factors have been established . Three of the most influential are age , sex , and race or ethnicity ( 1 , 7 - 9 ) . To better identify people at risk for obesity and those who might benefit from early intervention , we assessed the relationship between weight development and these influential factors . Despite the morbidity and mortality burden of obesity , its natural history has not been well characterized . Current knowledge is based largely on cross-sectional data . Although several large studies have examined weight development in adults , they have important limitations . Only a few tracked weight long enough to detect age-based trends . The first National Health and Nutrition Examination Survey ( NHANES I ) Epidemiologic Follow-up Study examined a representative group of U.S. residents but sample d only two time points , spaced 10 years apart , and had insufficient follow-up to track weight patterns in most minority groups ( 10 ) . The Coronary Artery Risk Development in Young Adults study followed weight development in a large cohort of young black and white Americans but did not provide data for other population s and was geographically restricted ( 8) . Other studies have been performed outside of the United States , but the results may not apply here ( 10 , 11 ) . We design ed our study to address the limitations described earlier . We examined data from the National Longitudinal Survey of Youth 1979 ( NLSY79 ) . This large , prospect i ve cohort study allowed longitudinal examination of weight trends over a time frame sufficient to capture the dynamics of such a slowly changing problem and of an age range during which obesity becomes prevalent . Because not all weight gain has been documented to be harmful , our analysis focused on obesity onset ( defined as the time at which a person reaches obesity ) rather than weight gain . We used the clinical definition of obesity ( BMI 30 kg/m2 ) as our end point because it reflects a point at which mortality risk increases substantially ( 12 ) . Underst and ing how obesity develops over time , who is at greatest risk , and when that risk is highest may be essential in reversing the population trend toward excess weight . Methods Study Group and Obesity Measurement We analyzed data from the NLSY79 , which was initiated by the U.S. Department of Labor , Bureau of Labor Statistics . This survey was design ed to gather information about the labor market activities and other life events of young U.S. citizens . It has been used extensively in economic and sociologic analyses , and the sample design is described elsewhere ( 13 - 16 ) . The cohort of men and women , born between 1957 and 1964 , has been followed for more than two decades . It consists of a nationally representative group , with supplemental sample s overrepresenting minority racial and ethnic groups and poor persons . We excluded a sample of military personnel because this population was removed from the study in 1985 and because physical activity requirements for these individuals could lead to atypical weight patterns . We included only persons who reported that the ethnicity with which they most closely identified was Hispanic , black , or white ( or European origin ) . Height and weight data were self-reported ; height was reported in 1981 and 1985 , and weight was reported 12 times between 1981 and 1998 . Examination of Age-Specific Body Mass Index Patterns Age-specific BMI was calculated for all participants . Height was assumed to remain constant after age 21 years . St and ard clinical definitions were used for overweight ( BMI 25 to 29.9 kg/m2 ) and obesity ( BMI 30 kg/m2 ) . Trends in age-specific BMI were examined by race or ethnicity and birth year . Cohort Differences We examined whether rates of obesity onset differed for people maturing at different times in our sample . Birth cohorts were grouped by 2-year increments . To st and ardize relative rates to age rather than calendar year , time was expressed as the number of years until a person reached obesity , starting from a st and ard age . In the cohort analysis , obesity onset was evaluated from age 24 years ( the baseline age of the oldest participants ) . The outcome of interest was obesity , and the time variable was years from age 24 years to obesity . People who were already obese at age 24 years were excluded . KaplanMeier plots visually demonstrated differences in rates of obesity onset . Cox proportional-hazards modeling estimated the ratio of rates ( hazard ratio ) between groups . For this method to be correct , the ratio of rates must be constant over time ( proportional ) . To assess this assumption , we used two methods : a statistical test of the scaled Schoenfeld residuals , with a P value greater than 0.05 implying that the rates were proportional and a visual method with parallel lines implying proportional rates . In all our analyses , results of proportional hazards testing were reported whenever the assumption was violated . Timing of Obesity Onset by Race or Ethnicity and Sex We evaluated relative rates of obesity onset in 17- and 18-year-old persons of different race or ethnicity who were not obese at the start of the study ; different models were used for men and women . Time was expressed as the number of years from age 17 years until reaching obesity . To control for birth cohort differences , models were adjusted for birth year . As before , KaplanMeier plots were examined and hazard ratios were estimated by using Cox proportional-hazards modeling . To determine relative importance of weight gain during childhood compared with adulthood in terms of the timing of obesity onset , we adjusted the models for baseline BMI at 17 or 18 years of age and examined the effect on hazard ratio estimation . Prevalence and Incidence of Obesity in Early Adulthood For this analysis , we defined early adulthood as the period from 20 to 22 years of age to 35 to 37 years of age . Persons born between 1959 and 1963 were queried about their weight one to two times during each of these age intervals . We calculated the prevalence and incidence of obesity across the early adulthood range . Logistic regression modeling predicted obesity status at age 35 to 37 years from an individual 's race or ethnicity , sex , and BMI at age 20 to 22 years . The model was adjusted in 2-year increments for year of birth . Its predictive ability was quantified by using receiver-operating characteristic ( ROC ) curves . This study was evaluated and exempted from review by the Institutional Review Board of the University of North Carolina at Chapel Hill . Role of the Funding Sources Primary funding was through the Robert Wood Johnson Clinical Scholars Program , with additional support from the National Institute of Child Health and Human Development . Neither entity had a role in the design , conduct , or reporting of this study . Results Description of the Study Sample The total sample included 9179 people : 19 % Hispanic , 31 % black , and 50 % white ( Table ) . People who did not report ethnicity ( n = 106 ) were not included . Age ( sample year minus birth year ) ranged from 17 to 24 years in 1981 to 34 to 41 years in 1998 , and participants were equally distributed across 8 years of birth . Baseline weight was 31.7 to 136.1 kg , and baseline BMI was 11.3 to 51.5 kg/m2 . Table . Sample Characteristics in 1981 Relationship of Body Mass Index to Time Mean age-specific BMI increased with time . This relationship between weight and time has two components , illustrated with data from the oldest and youngest birth cohorts of our sample ( Figure 1 ) . The first is the natural history of body weight : Average BMI increased with age throughout early adulthood . The second is a secular weight trend : Persons born in later calendar years tended to have larger age-specific BMI values . In every case in which the same age was sample d for both birth cohorts , the group born in 1957 had a lower mean BMI than the group born Objectives Obesity is a known risk factor for type 2 diabetes ( T2D ) . We conducted a case – control study to assess the association between body mass index ( BMI ) and the risk of being diagnosed with T2D in the United States . Methods We selected adults ( ≥ 18 years old ) who were diagnosed with T2D ( defined by ICD-9-CM diagnosis codes or use of anti-diabetic medications ) between January 2004 and October 2011 ( “ cases ” ) from an electronic health records data base provided by an integrated health system in the Middle Atlantic region . Twice as many individuals enrolled in the health system without a T2D diagnosis during the study period ( “ controls ” ) were selected based on age , sex , history of cardiac comorbidities or hyperinflammatory state ( defined by C-reactive protein and erythrocyte sedimentation rate ) , and use of psychiatric or beta blocker medications .  BMI was measured during one year prior to the first observed T2D diagnosis ( for cases ) or a r and omly assigned date ( for controls ) ; individuals with no BMI measure or BMI < 18.5 kg/m2 were excluded . We assessed the impact of increased BMI ( overweight : 25–29.9 kg/m2 ; Obesity Class I : 30–34.9 kg/m2 ; Obesity Class II : 35–39.9 kg/m2 ; Obesity Class III : ≥40 kg/m2 ) , relative to normal BMI ( 18.5–24.9 kg/m2 ) , on a T2D diagnosis using odds ratios ( OR ) and relative risks ( RR ) estimated from multiple logistic regression results . Results We included 12,179 cases ( mean age : 55 , 43 % male ) and 25,177 controls ( mean age : 56 , 45 % male ) . We found a positive association between BMI and the risk of a T2D diagnosis . The strength of this association increased with BMI category ( RR [ 95 % confidence interval ] : overweight , 1.5 [ 1.4–1.6 ] ; Obesity Class I , 2.5 [ 2.3–2.6 ] ; Obesity Class II , 3.6 [ 3.4–3.8 ] ; Obesity Class III , 5.1 [ 4.7–5.5 ] ) . Conclusions BMI is strongly and independently associated with the risk of being diagnosed with T2D . The incremental association of BMI category on the risk of T2D is stronger for people with a higher BMI relative to people with a lower BMI BACKGROUND Obesity , defined by a body-mass index ( BMI ) ( the weight in kilograms divided by the square of the height in meters ) of 30.0 or more , is associated with an increased risk of death , but the relation between overweight ( a BMI of 25.0 to 29.9 ) and the risk of death has been question ed . METHODS We prospect ively examined BMI in relation to the risk of death from any cause in 527,265 U.S. men and women in the National Institutes of Health-AARP cohort who were 50 to 71 years old at enrollment in 1995 - 1996 .  BMI was calculated from self-reported weight and height . Relative risks and 95 percent confidence intervals were adjusted for age , race or ethnic group , level of education , smoking status , physical activity , and alcohol intake . We also conducted alternative analyses to address potential biases related to preexisting chronic disease and smoking status . RESULTS During a maximum follow-up of 10 years through 2005 , 61,317 participants ( 42,173 men and 19,144 women ) died  . Initial analyses showed an increased risk of death for the highest and lowest categories of BMI among both men and women , in all racial or ethnic groups , and at all ages . When the analysis was restricted to healthy people who had never smoked , the risk of death was associated with both overweight and obesity among men and women . In analyses of BMI during midlife ( age of 50 years ) among those who had never smoked , the associations became stronger , with the risk of death increasing by 20 to 40 percent among overweight persons and by two to at least three times among obese persons ; the risk of death among underweight persons was attenuated . CONCLUSIONS Excess body weight during midlife , including overweight , is associated with an increased risk of death Background — Abdominal adiposity is a growing clinical and public health problem . It is not known whether it is similarly associated with cardiovascular disease ( CVD ) and diabetes mellitus in different regions around the world , and thus whether measurement of  waist circumference ( WC ) in addition to body mass index ( BMI ) is useful in primary care practice . Methods and Results — R and omly chosen primary care physicians in 63 countries recruited consecutive patients aged 18 to 80 years on 2 prespecified half days .  WC and BMI  were measured and the presence of CVD and diabetes mellitus recorded . Of the patients who consulted the primary care physicians , 97 % agreed to participate in the present study . Overall , 24 % of 69 409 men and 27 % of 98 750 women were obese ( BMI ≥30 kg/m2 ) . A further 40 % and 30 % of men and women , respectively , were overweight ( BMI 25 to 30 kg/m2 ) . Increased WC ( > 102 for men and > 88 cm for women ) was recorded in 29 % and 48 % , CVD in 16 % and 13 % , and diabetes mellitus in 13 % and 11 % of men and women , respectively . A statistically significant grade d increase existed in the frequency of CVD and diabetes mellitus with both BMI and WC , with a stronger relationship for WC than for BMI across regions for both genders . This relationship between WC , CVD , and particularly diabetes mellitus was seen even in lean patients ( BMI < 25 kg/m2 ) . Conclusions — Among men and women who consulted primary care physicians  , BMI and particularly WC were both strongly linked to CVD and especially to diabetes mellitus . Strategies to address this global problem are required to prevent an epidemic of these major causes of morbidity and mortality BACKGROUND Obese patients have favorable outcomes in congestive heart failure , hypertension , peripheral vascular disease , and coronary artery disease . Obesity also has been linked with increased incidence of atrial fibrillation , but its influence on outcomes in atrial fibrillation patients has not been investigated . The objective of this research is to investigate the effect of obesity on outcomes in atrial fibrillation . METHODS The Atrial Fibrillation Follow-up Investigation of Rhythm Management ( AFFIRM ) study was one of the largest multicenter trials of atrial fibrillation , with 4060 patients . Subjects were r and omized to rate versus rhythm-control strategy . We performed a post hoc analysis of the National Heart , Lung and Blood Institute limited access data set of atrial fibrillation patients who had body mass index ( BMI ) data available in the AFFIRM study . BMI data were not available on 1542 patients . Patients with BMI > or=18.5 were split into normal ( 18.5 - 25 ) , overweight ( 25 - 30 ) , and obese ( > 30 ) categories as per BMI ( kg/m(2 ) ) . Multivariate Cox proportional hazards regression was used on the eligible 2492 patients . End points were all-cause mortality and cardiovascular mortality . RESULTS Over three fourths of all patients in our cohort were overweight or obese . There were 304 deaths ( 103 among normal weight , 108 among overweight , and 93 among obese ) and 148 cardiovascular deaths ( 54 among normal weight , 41 among overweight , and 53 among obese ) over a mean period of 3 years of patient follow-up . On multivariate analysis , overweight ( hazard ratio [ HR ] 0.64 ; 95 % confidence interval [ CI ] , 0.48 - 0.84 ; P=.001 ) and obese ( HR 0.80 ; 95 % CI , 0.68 - 0.93 ; P=.005 ) categories were associated with lower all-cause mortality as compared with normal weight . Overweight ( HR 0.40 ; 95 % CI , 0.26 - 0.60 ; P < .001 ) and obese patients ( HR 0.77 ; 95 % CI , 0.62 - 0.95 ; P=.01 ) also had lower cardiovascular mortality as compared with the normal weight patients . CONCLUSIONS Although in prior studies , obesity has been associated with increased risk of atrial fibrillation , an obesity paradox exists for outcomes in atrial fibrillation . Obese patients with atrial fibrillation appear to have better long-term outcomes than nonobese patients Context : The benefit of weight reduction for cardiovascular disease ( CVD ) outcomes remains uncertain . Objective : To examine the effects of baseline body mass index on major CVD outcomes and diabetes over a 20 year follow up , and of weight change in the first five years over the subsequent 15 years . Design and setting : A prospect i ve study of British men followed up for 20 years . Participants : Men aged 40–59 years with no diagnosis of CVD or diabetes ( n = 7176 ) of whom 6798 provided full information on weight change five years later . Outcome measures : Major CVD events ( fatal and non-fatal myocardial infa rct ion and stroke , angina , “ other ” CVD deaths ) and diabetes . Results : During the 20 year follow up there were 1989 major CVD events and 449 incident cases of diabetes in the 7176 men . Risk of major CVD and diabetes increased significantly with increasing overweight and obesity . During the 15 year follow up , weight gain was associated with increased risk of CVD and diabetes . Weight loss was associated with lower risk of diabetes than the stable group irrespective of initial weight . No significant cardiovascular benefit was seen for weight loss in any men , except possibly in considerably overweight ( BMI 27.5–29.9 kg/m2 ) younger middle aged men ( RR = 0.42 ; 95 % CI 0.22 to 0.81 ) . Conclusion : Long term risk of CVD and diabetes increased significantly with increasing overweight and obesity . Weight loss was associated with significant reduction in risk of diabetes but not CVD , except possibly in considerably overweight younger men . Duration and severity of obesity seem to limit the cardiovascular benefits of weight reduction in older men PURPOSE An obesity paradox , a " paradoxical " decrease in morbidity and mortality with increasing body mass index ( BMI ) , has been shown in patients with heart failure and those undergoing percutaneous coronary intervention . However , whether this phenomenon exists in patients with hypertension and coronary artery disease is not known . METHODS A total of 22,576 hypertensive patients with coronary artery disease ( follow-up 61,835 patient years , mean age 66+/-9.8 years ) were r and omized to a verapamil-SR or atenolol strategy . Dose titration and additional drugs ( tr and olapril and /or hydrochlorothiazide ) were added to achieve target blood pressure control according to the Sixth Joint National Committee on Prevention , Detection , Evaluation , and Treatment of High Blood Pressure targets . Patients were classified into 5 groups according to baseline BMI : less than 20 kg/m2 ( thin ) , 20 to 25 kg/m2 ( normal weight ) , 25 to 30 kg/m2 ( overweight ) , 30 to 35 kg/m2 ( class I obesity ) , and 35 kg/m2 or more ( class II-III obesity ) . The primary outcome was first occurrence of death , nonfatal myocardial infa rct ion , or nonfatal stroke . RESULTS With patients of normal weight ( BMI 20 to<25 kg/m2 ) as the reference group , the risk of primary outcome was lower in the overweight patients ( adjusted hazard ratio [ HR ] 0.77 , 95 % confidence interval [ CI ] , 0.70 - 0.86 , P<.001 ) , class I obese patients ( adjusted HR 0.68 , 95 % CI , 0.59 - 0.78 , P<.001 ) , and class II to III obese patients ( adjusted HR 0.76 , 95 % CI , 0.65 - 0.88 , P < .001 ) . Class I obese patients had the lowest rate of primary outcome and death despite having smaller blood pressure reduction compared with patients of normal weight at 24 months ( -17.5+/-21.9 mm Hg/-9.8+/-12.4 mm Hg vs -20.7+/-23.1 mm Hg /-10.6+/-12.5 mm Hg , P<.001 ) . CONCLUSION In a population with hypertension and coronary artery disease , overweight and obese patients had a decreased risk of primary outcome compared with patients of normal weight , which was driven primarily by a decreased risk of all-cause mortality . Our results further suggest a protective effect of obesity in patients with known cardiovascular disease in concordance with data in patients with heart failure and those undergoing percutaneous coronary intervention Atrial fibrillation ( AF ) and obesity have reached epidemic proportions . The impact of obesity on clinical outcomes in patients with established AF is unknown . We analyzed 2,492 patients in the Atrial Fibrillation Follow-Up Investigation of Rhythm Management ( AFFIRM ) study .  Body mass index ( BMI ) was evaluated as a categorical variable ( normal 18.5 to < 25 kg/m(2 ) , overweight 25 to < 30 kg/m(2 ) , obese > or=30 kg/m(2 ) ) . Rate of death from any cause was higher in the normal BMI group ( 5.8 per 100 patient-years ) than in the overweight and obese groups ( 3.9 and 3.7 , respectively ) . Cardiovascular death rate was highest in the normal BMI group ( 3.1 per 100 patient-years ) , lowest in the overweight group ( 1.5 per 100 patient-years ) , and intermediate in the obese group ( 2.1 per 100 patient-years ) . After adjustment for baseline factors , differences in risk of death from any cause were no longer significant . However , overweight remained associated with a lower risk of cardiovascular death ( hazard ratio 0.47 , p = 0.002 ) . Obese patients were more likely to have an uncontrolled heart rate at rest , but rhythm-control strategy success was similar across BMI categories . In each BMI category , risk of death from any cause was similar for patients r and omized to a rhythm- or rate-control strategy . In conclusion , in patients with established AF , overweight and obesity do not adversely affect overall survival . Obesity does not appear to affect the relative benefit of a rate- or rhythm-control strategy BACKGROUND Obesity is associated with the development of atrial fibrillation and may impact atrial fibrillation-related outcomes . To date , no anthropometric measure is included in any risk stratification scheme for stroke and death in atrial fibrillation patients . METHODS The prospect i ve Danish Diet , Cancer and Health study is a cohort including 57,053 participants ( 27,178 men and 29,875 women ) aged between 50 and 64 years . The study population for this study included the 3135 patients ( 2025 men and 1110 women ) who developed incident atrial fibrillation during follow-up . RESULTS Of the subjects with atrial fibrillation , 1414 ( 45 % ) had a body mass index ( BMI ) in the overweight category ( BMI 25 to < 30 kg/m(2 ) ) and 767 ( 24 % ) were categorized as obese ( BMI ≥30 kg/m(2 ) ) . During a median follow-up of 4.9 years , 609 deaths and 216 thromboembolic events ( 98 % ischemic strokes ) occurred . Using normal-weight patients as reference , the risk of a composite end point of " ischemic stroke , thromboembolism , or death " was significantly higher in overweight ( crude hazard ratio [ HR ] 1.31 ; 95 % confidence interval [ CI ] , 1.09 - 1.56 ) and obese patients ( crude HR 1.55 ; 95 % CI 1.27 - 1.90 ) . After adjustment for CHADS2 and CHA2DS2-VASc scores , the HRs for the composite end point were 1.21 ( 95 % CI 1.02 - 1.45 ) and 1.31 ( 95 % CI 1.10 - 1.56 ) , respectively , for overweight and 1.25 ( 95 % CI 1.03 - 1.53 ) and 1.36 ( 95 % CI 1.11 - 1.65 ) , respectively , for obese . Continuous analyses of BMI stratified by sex identified obese men and normal-weight women as the sex-specific " high-risk " categories . CONCLUSION Overweight and obesity are risk factors for " ischemic stroke , thromboembolism or death " in patients with atrial fibrillation , even after adjustment for CHADS2 and CHA2DS2-VASc scores . The association between BMI and outcomes among atrial fibrillation patients may be modified by sex
This indicates that even in the absence of metabolic abnormalities , overweight and obesity are not innocuous , perhaps because the traditional cardiovascular risk factors are either not present early or remain undetected using routine clinical assessment .
This raises the concept that early or sub clinical organ damage assessment s may be better at identifying subjects who are more likely to progress to develop cardiovascular disease .
Obesity and Consequences The prevalence of overweight and obesity has reached epidemic proportion , with the recent figures from the World Health Organization indicating that in 2016 39 % of adults aged ≥18 years ( 39 % of men and 40 % of women ) were overweight and 13 % ( 11 % of men and 15 % of women ) obese .
The World Health Organization states that raised body mass index ( BMI ) is a major risk factor for noncommunicable diseases such as cardiovascular diseases ( mainly heart disease and stroke ) , which were the leading causes of death in 2012 , diabetes mellitus , musculoskeletal disorders , and some cancers .
The Framingham Heart Study data have indicated that overweight and obesity are associated with significantly decreased life expectancy .
Nevertheless , and against these strong evidence s , the relationship between BMI and mortality has been challenged by several studies , indicating a survival advantages for those who are overweight and class I obese .
However , the determinants of these observations are poorly understood and continue to be debated because BMI may not be the ideal index of adiposity and fat distribution and fitness and disease prevention may obscure the link between BMI and mortality .
Overweight or obesity is not always accompanied by traditional risk factors .
In fact , a systematic review and meta analysis revealed that about 35 % of obese individuals are metabolically healthy .
There is evidence that an important factor driving at least some of the obesity-associated end-organ damage is overactivity of the sympathetic nervous system ( SNS ) , an observation that suggests that targeting SNS in obesity may help reduce the cardiovascular risk associated with obesity .
In this review , we highlight the current knowledge of the potential role of SNS function in obesity-induced organ damage and examine whether interventions aim ed at reducing cardiovascular risk in obesity may be mediated via alterations in SNS activity .