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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Circ Cardiovasc Qual Outcomes. Author manuscript; available in PMC 2010 September 1.
Published in final edited form as:
PMCID: PMC2779550
NIHMSID: NIHMS139519

Trends in 10-year Predicted Risk of Cardiovascular Disease in the United States, 1976-2004

Francisco Lopez-Jimenez, M.D., MSc.,* John A. Batsis, M.D., Véronique L. Roger, M.D., M.P.H.,*# Lee Brekke, Ph.D.,+ Henry H. Ting, M.D., M.B.A.,* and Virend K. Somers, M.D., D.Phil.*

Abstract

Background

There have been significant bidirectional changes in the prevalence of cardiovascular (CV) risk factors over time in the United States, making the net trend in risk for incident CV disease unknown. We assessed these trends by applying the Framingham Heart Study prediction model on national data.

Methods and Results

The National Health and Nutrition Examination Surveys (NHANES) II (1976-1980), NHANES III (1988-1994), and NHANES 1999-2004 are cross-sectional, representative samples of the non-institutionalized population of the United States. We excluded people with a history of CV disease, pregnant women, participants with missing CV risk factors data and individuals outside the Framingham age range of 30-74 years. The Framingham risk function was used to estimate the 10-year risk for incident symptomatic CV disease. We calculated the slope of change or rate of change per year between NHANES II and III, and between NHANES III and 1999-2004. The difference between slopes was calculated and compared to zero. The average age-adjusted 10-year CV risk between NHANES II and III decreased from 10.0 to 7.9% between NHANES II and III with a statistically significant slope (P<0.001). However, the average age-adjusted CV risk decreased at a lesser magnitude between NHANES III and NHANES 1999-2004 from 7.9 to 7.4%, (P<0.001). These slopes were significantly different(p<0.0001). In women and middle-aged participants, CV risk did not change between NHANES III and NHANES 1999-2004 (P=0.40).

Conclusions

The estimated net risk for CV disease in the US population decreased from 1976-1980 to 1988-1994 but has changed minimally from 1988-1994 to 1999-2004, particularly in women and middle-aged people.

Keywords: obesity, epidemiology, prevention, risk factors

INTRODUCTION

Cardiovascular (CV) disease represents the most common cause of death in the United States, accounting for approximately one million deaths annually 1. Multiple reports have demonstrated significant changes in the prevalence of CV risk factors over the last 30 years, including downward trends in cholesterol 2 and cigarette smoking 3, 4, and an early decrease in the prevalence of hypertension for the last 10 years 5-9. There have also been increases in the prevalence of obesity10, 11 and diabetes mellitus12-14. Because these major CV risk factors provide different strengths of risk for incident myocardial infarction15, it is unknown if the net trend in risk for incident CV disease in the United States has increased, decreased or has remained stable over the last three decades.

Epidemiologic studies assessing the trend in CV disease incidence has demonstrated conflicting results in the incidence of myocardial infarction or coronary artery disease as a whole16. The ascertainment of temporal trends in incident CV disease is difficult. Major challenges include change in the diagnostic criteria for myocardial infarction, changes in physicians practice, the discovery of new methods in diagnosing preclinical coronary disease and the discovery and wide implementation of highly sensitive techniques in detecting myocardial injury. Despite the overwhelming evidence demonstrating a decrease in age-adjusted CV mortality over the last decades17-19, it is unclear if the bidirectional trends in CV risk factors are reflected in a reduced risk for incident CV disease.

Validated risk prediction formulas can estimate individual coronary risk20. The formulas or algorithms are based on predictive modeling which has been extensively validated in different populations in the US 20, 21 and elsewhere22, 23. These prediction formulas provide reliable estimates of global population risk and help in identifying changes in net CV risk.

Using data from three consecutive population-based health surveys in the United States over the past 30 years, we assessed the trends in the net 10-year-risk for incident CV disease using the Framingham Coronary Heart Disease risk score20. We hypothesized that 10-year risk for incident CV disease has decreased between 1976-1980 and 1988-1994, but remained unchanged between 1988-1994 and 1999-2004 due to the significant increase in the prevalence of obesity and obesity-related CV risk factors.

METHODS

Study population

The National Health and Nutrition Examination Survey (NHANES) are three cross-sectional surveys representative of non-institutionalized people in the US. The present analysis incorporated major CV risk factors from NHANES II (1976-1980), NHANES III (1988-1994), and NHANES 1999-2004, all collected in a standardized manner. Detailed study design and sampling have been described previously 24-30.

Because our focus was to estimate the 10-year-risk for incident CV disease, we excluded people with a self reported history of myocardial infarction, angina, or stroke; pregnant women; people with missing CV risk factor data; individuals >74 years as they were not included in NHANES II; and subjects <30 years as the Framingham score was not designed to assess risk in this age group. Of participants with non-zero weights, we excluded 2,310 participants of a total of 9,237 in NHANES II, 1800 participants of 11,137 from NHANES III, and 1836 participants of 9702 from NHANES 1999-2004. There were a total of 6,927 participants, 9,337 participants, and 7,866 participants used from each respective survey in the risk function. The subset of patients with fasting data included 3,463 patients for NHANES II, 4,494 from NHANES III, and 7,866 from NHANES 1999-2004. NHANES III and NHANES 1999-2004 underwent formal institutional review board approval that included a written informed consent. NHANES II did not have formal institutional review in the manner in which it is defined currently. This analysis obtained an exemption from the Institutional Review Board as the data was de-identified in nature.

Measurements

Lipid analyses were conducted on frozen serum samples shipped on dry ice to a central laboratory31. Cholesterol measurements were standardized according to the Centers for Disease Control-National Heart, Lung and Blood Institute Lipid Standardization Program criteria 31. We used different definitions of dyslipidemia depending of the parameter used and history of treatment. High cholesterol was defined as a measured total cholesterol (TChol) ≥240 mg/dL. Dyslipidemia was defined as participants having a total cholesterol (TChol) ≥240 mg/dL; or a high density lipoprotein cholesterol (HDL) ≤40 mg/dL in men or ≤50 mg/dL in women. Finally, “Dyslipidemia with TG” included participants with a diagnosis of dyslipidemia with a triglyceride (TG) level of ≥150mg/dL whose blood results were based on a morning subsample of blood. We also classified participants according to the history of self-reported dyslipidemia and treatment for it. These definitions paralleled those outlined by the National Cholesterol Education Program – Adult Treatment Panel III guidelines32.

Plasma glucose was measured using the hexokinase enzymatic method 13, 33. Diabetes prevalence was defined as the sum of the number or participants with self-reported diabetes on the whole sample combined with those with glucose level ≥126 mg/dL on the fasting morning sub-sample using methods of Flegal et al 34, and termed “prevalent diabetes.” This calculation includes variance calculations using jackknife methods accounting for dependence between the two samples 34, 35. This definition of diabetes was based on the most recent ADA consensus statement36 and was slightly different than the definition used in the Framingham study20, where the cutoff value for fasting glucose was 150 mg/dl. However, the CV risk associated with a fasting glucose between 126 to 150 is very similar than the risk of glucose values just above 150 mg/dl. Undiagnosed diabetes was defined as a fasting glucose of ≥126mg/dL36 and absence of self-reported diabetes.

Differences in blood pressure measurement protocol across the three surveys included the number of measurements, the qualifications of the staff performing them, and if it was measured in seated or supine positions. We limited our analysis to sitting measurements. The first measurement was excluded unless it was the only one available and the remaining measurements were averaged to conform to procedures used in NHANES 1999-2004. We defined “history of hypertension” as a self-reported diagnoses of hypertension and defined “Hypertension-measured” if systolic blood pressure was ≥140 mm/Hg or diastolic blood pressure was ≥90 mm/Hg, regardless of the presence of self-reported hypertension or current hypertension treatment. This was performed in line with the manner the Framingham 10-year risk score incorporates blood pressure values. This model does not differentiate between diagnosed vs undiagnosed hypertension, or between those receiving treatment for hypertension vs those untreated. We also analyzed the prevalence of treated hypertension.

Current smoking was defined as current cigarette, pipe, or cigar smoker. Current cigarette smoking was defined if subjects answered yes to both questions: “Have you smoked at least 100 cigarettes in your entire life?” and “Do you smoke cigarettes now?” Current cigar or pipe smoking was defined if participants smoked either type “every day” or “some days”. The NHANES definition of current smoking was slightly different than the Framingham study20, where current smoking was defined as smoking regularly during the previous 12 months.

Weight and height were measured by standard protocols. Body mass index (BMI) was calculated by dividing the weight in kilograms by the square of height in meters. Obesity was defined as BMI ≥30kg/m2.

NHANES Data

Data and documentation for all surveys were downloaded in September/October 2006 from the NHANES website37. Combined sampling weights for NHANES 1999-2004 were created according to guidelines38. Age groups consisting of ages 30-40, 40-50, and 60-74 were defined for trend comparisons as recommended by NHANES III 39.

Coronary Heart Disease Risk Function

We used the Framingham formula 20 to estimate the 10-year risk for incident coronary disease, separately by gender, using: age, TChol, HDL, blood pressure (5 categories each); diabetes (yes/no) and smoking (yes/no). The crude score was calculated based on the linear function consisting of the sum of beta coefficients, and transformed into 10-year predicted CV disease risk. The risk score was used in statistical tests of change as it had a less skewed distribution than the 10-year risk itself. CV risk was additionally calculated as if all members were 50 years old.

Analysis

We calculated weighted means, standard errors, and 95% confidence limits using SAS-callable SUDAAN 9.0.1 to properly account for the complex survey design. The NHANES examination sample weight was used for most variables. The morning fasting sample weight was used for the sub-sample with values for fasting glucose, low density lipoprotein cholesterol (LDL), and TGs. Triglyceride values were converted to their natural log during the analyses because of the considerable skewness of the variable.

Results were age-gender standardized by the direct method to the actual results of the US Census 2000 population40, 41. We did not use the Year 2000 age-adjustment weights that are commonly used in mortality estimates, because these weights are based on the predicted US population in year 2000 and not on actual values. The age groups used for standardization were 30-40, 40-49, 50-59, and 60-74 years. This standardization also served to adjust for missing data by age and gender. For trend analyses we used F-tests. Our primary outcome was the slope of change or rate of change per year between NHANES II and III (first time period), and between NHANES III and 1999-2004 (second time period). For each survey we used the timeframe between the mid points to measure the elapsed time between surveys, using 13 years as the average time between the first two surveys and 10.5 years between the last two. The difference in slopes was also calculated and compared to zero using a t-test. A P-value <0.05 was considered statistically significant. The authors had full access to the data and take responsibility for its integrity. All authors have read and agree to the manuscript as written.

RESULTS

Table 1 represents the general characteristics of participants during the three NHANES surveys, standardized to the United States 2000 Census, and demonstrates the change in slope between NHANES II and NHANES III and between NHANES III and NHANES 1999-2004 and the difference between the slopes. Figures 1 and and22 show the prevalence change in each of the five major CV risk factors over the course of the surveys.

Figure 1
Overall Trends in Cardiovascular Risk Factors – Males
Figure 2
Overall Trends in Cardiovascular Risk Factors – Females
Table 1
Overall Trends of Baseline Characteristics with each Survey over Time

Obesity

The prevalence of obesity rose during each time period, a trend similar in both sexes. The mean BMI increased in all age groups, as did the proportion with a BMI≥30 kg/m2, but the rate was higher in females than males. The rate of change was similar in both time periods.

Hypertension

The prevalence of participants with an elevated blood pressure (those defined as hypertension-measured) significantly decreased over time, but the decrease was more significant in the first time period than in the second period for the overall cohort, in either sex and across all age groups. The proportion of participants on hypertensive medications increased significantly over time. The mean values of systolic blood pressure dropped in all age groups in the first time period, but increased slightly in period two. Detailed changes in blood pressure values over time for the whole group and comparisons of slopes are listed in Table 1. Values separated by sex or age group are displayed in Appendix 1 and 2.

Hyperlipidemia

The mean TChol decreased during the first time period but the mild decline in the second period did not reach statistical significance, while LDL steadily decreased during both periods. Mean HDL showed a modest increase over time, but the slope was statistically significant only during the second time period, in line with the significant rise in the use of medications for dyslipidemia42. Triglycerides had a non-significant increase over both time periods and in all groups. Changes over time in the prevalence of dyslipidemia using different definitions and the corresponding slopes are listed in Table 1. Values separated by sex or age group are displayed in Appendix 1 and 2.

Hyperglycemia and Diabetes

The rate of change for fasting glucose of all persons had a positive slope in the first time period (P<0.001) but in the second time period the change was insignificant. These trends were similar across sex and age groups. The rate of change for the percent of participants with diabetes mellitus had results parallel to those found for fasting glucose.

Smoking

The proportion of current smokers, cigarette, cigar and pipe smokers all decreased over time in both sexes and age groups. The rate of change was more pronounced in the first time period than in the second for the whole sample. Although the proportion of 30-49 and 50-59 year olds cigar smokers dropped in the first time period, there was a slight increase in the rate of smokers in the second time period.

Cardiovascular Risk

The average age-adjusted 10-year CV risk between NHANES II and NHANES III decreased from 10.0 to 7.9% with a statistically significant slope (P<0.001) (Figure 3). However, the average age-adjusted CV risk showed a smaller decrease between NHANES III and NHANES 1999-2004 from 7.9 to 7.4%, (P<0.001). The slope between both periods was significantly higher in the first time period than in the second. (P<0.001). Trends were nearly identical when data were analyzed assuming that all participants were 50 years old.

Figure 3
Trend in Overall 10-year Cardiovascular Disease Risk

When categorized by sex, CV disease risk in women decreased between NHANES II and NHANES III (P<0.001) but did not change between NHANES III and NHANES 1999-2004 (P=0.40). In contrast, men had a trend in CV risk similar to the entire sample (Figure 4). People from 60-74 years of age were the only age group with a decrease in predicted CV disease risk of similar magnitude in both time periods (Figure 5). For other age groups, the predicted risk decreased primarily between NHANES II and III but minimally between NHANES III and 1999-2004. These trends persisted in our sex-adjusted analysis and analysis of patients assuming to be 50 years of age (data not shown).

Figure 4
Trend in Cardiovascular Disease Risk by Sex
Figure 5
Trend in Cardiovascular Risk by Age

DISCUSSION

Our results, based on data from national surveys representative of the United States population, demonstrate that CV risk factors have changed at different rates and directions in the last 30 years. The net 10-year risk for incident CV disease in the United States has significantly decreased from 1976-1980 to 1990-1994, but has changed minimally thereafter. In women, there was no change in the latter period. Our results suggest that the stagnation of CV risk reduction can be explained by the slower improvement in lipid parameters and smoking rates, by the reversal of the trend in blood pressure control, and probably by the effect of the increased prevalence in obesity-related CV risk factors.

To the best of our knowledge, the current study is the first to calculate the trend in the net CV risk for developing CV disease over the last three decades. This period of time is when most evidence-based strategies for primary prevention of CV disease have emerged and been widely implemented 17.

These data have enormous public health implications, and suggest that the gain in primary prevention of CV disease that occurred from 1976-1980 to 1990-1994 has leveled off during the last time period, despite the discovery and implementation of effective treatment modalities in managing dyslipidemia and hypertension 8, 32, 43, national anti-smoking campaigns 44 and efforts related to primordial prevention. Our results also suggest that the lack of change of the net risk for incidental symptomatic CV disease may be due to the increased prevalence of obesity 10, 11 which translates into a higher prevalence of diabetes mellitus 13, 14 perhaps also contributing to the reversal of the trend in blood pressure control and the slower improvement in lipid parameters. If the obesity epidemic is sustained 45 and smoking rates, blood pressure, and lipid values continue with similar trajectories, the net population CV risk can be expected to increase.

It is difficult to determine whether our results will translate into a larger number of cardiovascular events in the United States in the coming years. However, the predicted reduction in the 10-year risk for incident CV disease from 1976-1980 to 1990-1994 shown in the present report was consistent with the modest decrease in incident CV disease observed in surveillance studies comparing CV disease rates between the 80s and the late 90s 46. This parallelism between the predicted reduction in risk and the reduction in events about 10 years later adds validity to our results.

Several studies have assessed temporal changes in individual CV risk factors, and their results have been in most part similar to ours, despite the fact that our analysis was limited to those without history of coronary disease or stroke and excluded young adults or those older than 74 years 2, 3, 8, 10, 13, 47. Our results confirm the previous observation that the early declines in adult smoking rates might be halted 3, 4. This study also agrees with others demonstrating the increased prevalence of cigar smoking in the last decade 45, which may explain the minimal reduction of overall smoking during the latter period, compared to the first time period.

Hajjar commented in 2003 that the prevalence of hypertension might be increasing despite a prior analysis from NHANES suggesting hypertension prevalence was declining 8. Our results support the concept that hypertension has had a bidirectional trend over the last 30 years manifested by a decline in systolic blood pressure values from NHANES II and NHANES III and a rise in these values between NHANES III and NHANES 1999-2004, despite better rates of awareness and wider use of antihypertensive medications.

Other reports have described the secular trends in serum lipids from 1960-2002, demonstrating that mean TChol and LDL levels have steadily decreased without significant changes in HDL and serum TG levels 2. Conversely, our results illustrate a modest secular increase in HDL, particularly between 1988-1994 to 1999-2004. Several factors may have contributed to lipid parameter improvement including enhanced screening for dyslipidemia and higher use of medications for dyslipidemia which can decrease TChol and LDL but also raise HDL. Dietary changes, particularly a reduction in saturated fat intake with mild increases in monounsaturated fat intake, may also explain the increase in mean HDL. Because exercise levels have remained unchanged 48, 49, the modest improvement in HDL could not be attributed to changes in physical activity.

Several studies have highlighted the increased prevalence of diabetes mellitus since 1976, particularly diagnosed diabetes, with little change in the prevalence of undiagnosed diabetes 13, 50. Our analysis also shows a significant increase in the average fasting blood plasma glucose levels over time, suggesting that the increase in the prevalence of diabetes mellitus reported elsewhere is not positively confounded due to changes in diagnostic criteria.

The limitations of the current study relate primarily to the intrinsic limitations of the NHANES surveys and that of the Framingham prediction model. As in any survey, participating bias may have yielded a sample that is not entirely representative of the population. However, specific to NHANES is that the nationally represented population excluded participants residing in nursing facilities, members of the armed forces, institutionalized participants or nationals living abroad. Hence generalizing the results to these populations should be made with caution. The survey was designed specifically to oversample certain subgroups of public health interest in order to increase the reliability and precision of health estimates for these groups. In addition, excluded patients may have differed from those included in this study. Some measurements may have differed by survey stage, and our efforts to standardize values might not be able to create identical variables. We acknowledge that many NHANES variables, including those assessing CV disease, are self-reported and may lead to reporting bias. The definition of diabetes and current smoking in the Framingham study were slightly different than the definitions used in the current analysis. Finally, although the Framingham risk score was developed for people with no history of CV disease, a small fraction of the total sample might have failed to report history of CV disease and were included in the current analysis. Although several of these limitations may hamper the validity of risk estimates in each NHANES survey, these potential sources of bias and error were present in the three surveys. Therefore, the comparison of trends in risk may be less affected than the individuals risk estimates.

Our analysis has several strengths. Contrary to other reports addressing the change in several CV risk factors, we used widely validated risk scores to predict the risk of incident symptomatic CV disease. By measuring the net change in CV risk, we can better estimate the global impact of preventive strategies, particularly when certain risk factors improve, others do not change, and others worsen during the same time period. NHANES data were obtained using a prospective methodology with standardized measurements and definitions, and are known to be representative of the US population. Even risk functions derived from NHANES data have accurately projected the extent of CV events and overall mortality in other population groups 51, 52. Furthermore, only one other study has evaluated the change in CV risk among United States adults but only used two NHANES surveys, and relied on the risk model adopted by the National Cholesterol Education Program Adult Treatment Panel III and not the precise Framingham formula in estimating overall CV disease risk, and their results were not age-stratified 53.

The Framingham risk score does not account for risk factors such as family history of premature coronary disease, exercise, diet, obesity or body fat distribution. Nevertheless, at the time the scoring system was developed, exercise, obesity, and diet were believed to impact and mediate CV risk through factors already included in the model. Hence, our findings may actually be conservative risk estimates, as the increasing prevalence of obesity may have led to higher CV risk, not only mediated through commonly recognized cardiac risk factors, but also via obstructive sleep apnea, high leptin and low adiponectin levels, and changes in other inflammatory cytokines and adipokines linked with central obesity 54. Additionally, the Framingham risk score was created to help clinicians identify patients at high risk for CV disease and therefore simplicity has been a priority even if that requires sacrificing a small incremental predictive value with the use of the other risk factors.

The Framingham risk score was derived from a community sample of Caucasian subjects while the population included in NHANES overrepresents minorities. The validity of Framingham and other scores predicting CV disease has been tested in diverse populations and shown different event rates for any given estimated risk value. Although this weakness has been addressed and can be partially corrected by doing appropriate calibration, 21 the validity of the overall estimated risk may be limited. Moreover, CV risk prediction rules can help to predict changes in event rates after changes in different CV risk factors occur. For example, in an analysis showing the change in predicted CV risk in a sample of patients who underwent bariatric surgery 51, 55, the predicted reduction of cardiovascular events was very close to the risk reduction subsequently reported in a prospective cohort of people who underwent bariatric surgery 52. It has also been shown that the use of risk factor categories provides similar prognostic information as using non-categorical prediction functions. The score uses blood pressure and lipid values regardless of history of diagnosis or medical treatment for hypertension or dyslipidemia respectively. Blood pressure and cholesterol values regardless of use of medications better capture the impact of public health and clinical factors that may change over time, and are also less susceptible to recall bias than definitions based on treatment status. The prognostic performance of Framingham could affect the absolute risk estimates but not the trend over time because the same limitations will apply to the three time periods. Therefore, our main findings and conclusions are not hampered by the limitations inherent to the Framingham risk score.

In conclusion, our study has shown that the estimated net risk for CV disease in the United States population decreased from 1976-1980 to 1988-1994, but has changed minimally from 1988-1994 to 1999-2004. The net CV risk has remained unchanged in women from 1988-1994. Cardiovascular risk reduction has been maintained in patients aged 60 or greater, but the difference in risk reduction observed from NHANES II and III has been minimal in younger people, especially among those age 30-39. The increase in the prevalence of diabetes and in blood pressure levels may explain the staggering of the risk reduction from NHANES III to NHANES 1999-2004. Because obesity may predispose to diabetes mellitus 14 and can aggravate systemic blood pressure and dyslipidemia, the attenuation in risk reduction can be at least partially attributed to the growing epidemic. However, other factors like the attenuation in the reduction of prevalent smoking and cholesterol control observed in the second time period compared to the first one might also explain the results. These results reinforce the need for aggressive community-wide and office-based promotion of primordial prevention, with emphasis on physical activity, exercise, dietary changes aiming for a higher intake of fruits and vegetables, lower intake of salt and saturated fat, maintenance of a healthy weight and smoking control. These results also underscore the key role of health care providers managing CV risk factors. These findings confirm that the discovery and use of effective medications for lipids and blood pressure do not translate into global risk reduction, unless they are paired with strategies preventing the occurrence of diabetes, hypertension and dyslipidemia, and reducing the rates of new smokers.

What is known

  • Cardiovascular disease represents the most common cause of death in the United States
  • Hypertension and dyslipidemia have been well controlled through primary prevention measures
  • An increasing prevalence of diabetes and obesity has paralleled this decline
  • Validated cardiovascular risk prediction formulas can estimate individual coronary risk

What this article adds

  • Cardiovascular risk factors have changed at different rates in the past 30 years
  • The net 10-year risk for incident cardiovascular disease in the United States decreased significantly from 1976-1980 to 1990-1994, but changed minimally thereafter
  • Impact of diminishing change in risk likely attributed by slower improvements in lipid management and smoking rates, but probably due to the effect of an increasing prevalence of diabetes and obesity

Supplementary Material

Acknowledgments

FUNDING SOURCES Dr. Lopez-Jimenez was a recipient of a Clinical Scientist Development Award from the American Heart Association. Dr. Roger is supported by grants from the National Institutes of Health (HL 59205 and HL 72435). Dr. Somers is supported by grants from the National Institutes of Health (HL-65176, HL-70302, HL-73211, and M01-RR00585).

ABBREVIATIONS

BMI
Body mass index
CV
Cardiovascular
HDL
High density lipoprotein cholesterol
LDL
Low density lipoprotein cholesterol
NHANES
National Health and Nutrition Examination Survey
TChol
Total cholesterol
TG
Triglycerides

Footnotes

Work was presented in part at the American Heart Association Scientific Sessions, New Orleans, LA, November 7th-12th, 2008.

DISCLOSURES There are no conflicts of interest or disclosures relevant to the subject of this manuscript.

References

1. Rosamond W, Flegal K, Furie K, Go A, Greenlund K, Haase N, Hailpern SM, Ho M, Howard V, Kissela B, Kittner S, Lloyd-Jones D, McDermott M, Meigs J, Moy C, Nichol G, O’Donnell C, Roger V, Sorlie P, Steinberger J, Thom T, Wilson M, Hong Y. Heart disease and stroke statistics--2008 update: a report from the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Circulation. 2008;117:e25–146. [PubMed]
2. Carroll MD, Lacher DA, Sorlie PD, Cleeman JI, Gordon DJ, Wolz M, Grundy SM, Johnson CL. Trends in serum lipids and lipoproteins of adults, 1960-2002. Jama. 2005;294:1773–1781. [PubMed]
3. Husten CG, Shelton DM, Chrismon JH, Lin YC, Mowery P, Powell FA. Cigarette smoking and smoking cessation among older adults: United States, 1965-94. Tob Control. 1997;6:175–180. [PMC free article] [PubMed]
4. Tobacco use among adults--United States, 2005. MMWR Morb Mortal Wkly Rep. 2006;55:1145–1148. [PubMed]
5. Burt VL, Cutler JA, Higgins M, Horan MJ, Labarthe D, Whelton P, Brown C, Roccella EJ. Trends in the prevalence, awareness, treatment, and control of hypertension in the adult US population. Data from the health examination surveys, 1960 to 1991. Hypertension. 1995;26:60–69. [PubMed]
6. Cutler JA, Sorlie PD, Wolz M, Thom T, Fields LE, Roccella EJ. Trends in hypertension prevalence, awareness, treatment, and control rates in United States adults between 1988-1994 and 1999-2004. Hypertension. 2008;52:818–827. [PubMed]
7. Fields LE, Burt VL, Cutler JA, Hughes J, Roccella EJ, Sorlie P. The burden of adult hypertension in the United States 1999 to 2000: a rising tide. Hypertension. 2004;44:398–404. [PubMed]
8. Hajjar I, Kotchen TA. Trends in prevalence, awareness, treatment, and control of hypertension in the United States, 1988-2000. Jama. 2003;290:199–206. [PubMed]
9. Mosterd A, D’Agostino RB, Silbershatz H, Sytkowski PA, Kannel WB, Grobbee DE, Levy D. Trends in the prevalence of hypertension, antihypertensive therapy, and left ventricular hypertrophy from 1950 to 1989. N Engl J Med. 1999;340:1221–1227. [PubMed]
10. Flegal KM, Carroll MD, Kuczmarski RJ, Johnson CL. Overweight and obesity in the United States: prevalence and trends, 1960-1994. Int J Obes Relat Metab Disord. 1998;22:39–47. [PubMed]
11. Ogden CL, Carroll MD, Curtin LR, McDowell MA, Tabak CJ, Flegal KM. Prevalence of overweight and obesity in the United States, 1999-2004. Jama. 2006;295:1549–1555. [PubMed]
12. Harris MI, Eastman RC, Cowie CC, Flegal KM, Eberhardt MS. Comparison of diabetes diagnostic categories in the U.S. population according to the 1997 American Diabetes Association and 1980-1985 World Health Organization diagnostic criteria. Diabetes Care. 1997;20:1859–1862. [PubMed]
13. Harris MI, Flegal KM, Cowie CC, Eberhardt MS, Goldstein DE, Little RR, Wiedmeyer HM, Byrd-Holt DD. Prevalence of diabetes, impaired fasting glucose, and impaired glucose tolerance in U.S. adults. The Third National Health and Nutrition Examination Survey, 1988-1994. Diabetes Care. 1998;21:518–524. [PubMed]
14. Geiss LS, Pan L, Cadwell B, Gregg EW, Benjamin SM, Engelgau MM. Changes in incidence of diabetes in U.S. adults, 1997-2003. Am J Prev Med. 2006;30:371–377. [PubMed]
15. Vasan RS, Sullivan LM, Wilson PW, Sempos CT, Sundstrom J, Kannel WB, Levy D, D’Agostino RB. Relative importance of borderline and elevated levels of coronary heart disease risk factors. Ann Intern Med. 2005;142:393–402. [PubMed]
16. Roger VL, Jacobsen SJ, Weston SA, Goraya TY, Killian J, Reeder GS, Kottke TE, Yawn BP, Frye RL. Trends in the incidence and survival of patients with hospitalized myocardial infarction, Olmsted County, Minnesota, 1979 to 1994. Ann Intern Med. 2002;136:341–348. [PubMed]
17. Ford ES, Ajani UA, Croft JB, Critchley JA, Labarthe DR, Kottke TE, Giles WH, Capewell S. Explaining the decrease in U.S. deaths from coronary disease, 1980-2000. N Engl J Med. 2007;356:2388–2398. [PubMed]
18. Ford E, Giles W, Mokdad A. The Distribution of 10-Year Risk for Coronary Heart Disease Among US Adults. J Am Coll Cardiol. 2004;43:1791–1796. [PubMed]
19. McGovern PG, Jacobs DR, Jr, Shahar E, Arnett DK, Folsom AR, Blackburn H, Luepker RV. Trends in acute coronary heart disease mortality, morbidity, and medical care from 1985 through 1997: the Minnesota heart survey. Circulation. 2001;104:19–24. [PubMed]
20. Wilson PW, D’Agostino RB, Levy D, Belanger AM, Silbershatz H, Kannel WB. Prediction of coronary heart disease using risk factor categories. Circulation. 1998;97:1837–1847. [PubMed]
21. D’Agostino RB, Sr, Grundy S, Sullivan LM, Wilson P. Validation of the Framingham coronary heart disease prediction scores: results of a multiple ethnic groups investigation. Jama. 2001;286:180–187. [PubMed]
22. Liu J, Hong Y, D’Agostino RB, Sr, Wu Z, Wang W, Sun J, Wilson PW, Kannel WB, Zhao D. Predictive value for the Chinese population of the Framingham CHD risk assessment tool compared with the Chinese Multi-Provincial Cohort Study. Jama. 2004;291:2591–2599. [PubMed]
23. Guckelberger O, Mutzke F, Glanemann M, Neumann UP, Jonas S, Neuhaus R, Neuhaus P, Langrehr JM. Validation of cardiovascular risk scores in a liver transplant population. Liver Transpl. 2006;12:394–401. [PubMed]
24. US Department of Health and Human Services, National Center for Health Statistics. The Third National Health and Nutrition Examination Survey (NHANES III, 1988-1994) Centers for Disease Control and Prevention; Washington, DC: 1996.
25. Plan and operation of the health and nutrition examination survery. United States 1971-1977. Vital Health Stat. 1973;1:10b:11-46–10b:11-77.
26. Kuczmarski RJ, Flegal KM, Campbell SM, Johnson CL. Increasing prevalence of overweight among US adults. The National Health and Nutrition Examination Surveys, 1960 to 1991. Jama. 1994;272:205–211. [PubMed]
27. US Department of Health and Human Services. National Center for Health Statistics. NHANES III Anthropometric Procedure Video Stock no. 017-022-01355. Government Printing Office; Washington DC: 1996.
28. Guo SS, Wu W, Chumlea WC, Roche AF. Predicting overweight and obesity in adulthood from body mass index values in childhood and adolescence. Am J Clin Nutr. 2002;76:653–658. [PubMed]
29. Plan and operation of the Third National Health and Nutrition Examination Survey, 1988-94. Series 1: programs and collection procedures. Vital Health Stat 1. 1994:1–407. [PubMed]
30. Kuczmarski RJ. Bioelectrical impedance analysis measurements as part of a national nutrition survey. Am J Clin Nutr. 1996;64:453S–458S. [PubMed]
31. Myers GL, Cooper GR, Winn CL, Smith SJ. The Centers for Disease Control-National Heart, Lung and Blood Institute Lipid Standardization Program. An approach to accurate and precise lipid measurements. Clin Lab Med. 1989;9:105–135. [PubMed]
32. Executive Summary of The Third Report of The National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, And Treatment of High Blood Cholesterol In Adults (Adult Treatment Panel III) Jama. 2001;285:2486–2497. [PubMed]
33. Johnson CL, Rifkind BM, Sempos CT, Carroll MD, Bachorik PS, Briefel RR, Gordon DJ, Burt VL, Brown CD, Lippel K, et al. Declining serum total cholesterol levels among US adults. The National Health and Nutrition Examination Surveys. Jama. 1993;269:3002–3008. [PubMed]
34. Flegal KM, Ezzati TM, Harris MI, Haynes SG, Juarez RZ, Knowler WC, Perez-Stable EJ, Stern MP. Prevalence of diabetes in Mexican Americans, Cubans, and Puerto Ricans from the Hispanic Health and Nutrition Examination Survey, 1982-1984. Diabetes Care. 1991;14:628–638. [PubMed]
35. McGinn TG, Guyatt GH, Wyer PC, Naylor CD, Stiell IG, Richardson WS. Users’ guides to the medical literature: XXII: how to use articles about clinical decision rules. Evidence-Based Medicine Working Group. Jama. 2000;284:79–84. [PubMed]
36. Screening for type 2 diabetes. Diabetes Care. 2003;26(Suppl 1):S21–24. [PubMed]
37. Centers for Disease Control and Prevention (CDC). National Center for Health Statistics (NCHS) The National Health and Nutrition Examination Survey Data. Hyattsville, MD: US Department of Health and Human Services, Centers for Disease Control and Prevention; Http://www.cdc.gov/nchs/about/major/nhanes/datalink.htm.
38. Analytic and Reporting Guidelines, The National health and Nutrition Examination Survey (NHANES) National Center for Health Statistics, Centers for Disease Control and Prevention; Hyattsville, Maryland: Last Update: December 2005, Last Correction, September, 2006.
39. Analytic and Reporting Guidelines: The Third National Health and Nutrition Examination Survey, NHANES III (1988-94) National Center for Health Statistics, Centers for Disease Control and Prevention; Hyattsville, Maryland: Oct, 1996.
40. United States Department of Commerce, US Census Bureau, Population Division; Census Population 1970-2000, for Public Health Research, CDC WONDER On-line Database. Centers for Disease Control and Prevention (CDC), National Center for Health Statistics (NCHS); Mar, 2003.
41. Bridged-Race Population Estimates, United States, 1990-2003, July 1st resident population, by state, county, age, sex, race, and Hispanic origin, on CDC WONDER Online Database. 2005 June; Query Date: October 13th, 2006.
42. Mann D, Reynolds K, Smith D, Muntner P. Trends in statin use and low-density lipoprotein cholesterol levels among US adults: impact of the 2001 National Cholesterol Education Program guidelines. Ann Pharmacother. 2008;42:1208–1215. [PubMed]
43. Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL, Jr, Jones DW, Materson BJ, Oparil S, Wright JT, Jr, Roccella EJ. The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. Jama. 2003;289:2560–2572. [PubMed]
44. US Preventative Services Task Force. Counseling to Prevent Tobacco-Related Diseases: Recommendation Statement. Agency for Healthcare Research and Quality; Rockville, MD: Novermber, 2003. http://www.ahrq.gov/clinic/uspstf/uspstbac.htm.
45. Wang Y, Beydoun MA. The obesity epidemic in the United States--gender, age, socioeconomic, racial/ethnic, and geographic characteristics: a systematic review and meta-regression analysis. Epidemiol Rev. 2007;29:6–28. [PubMed]
46. Arnett DK, McGovern PG, Jacobs DR, Jr, Shahar E, Duval S, Blackburn H, Luepker RV. Fifteen-year trends in cardiovascular risk factors (1980-1982 through 1995-1997): the Minnesota Heart Survey. Am J Epidemiol. 2002;156:929–935. [PubMed]
47. Flegal K, Carrol M, Ogden C, Johnson C. Prevalence and Trends in Obesity Among US Adults, 1999-2000. JAMA. 2002;288:1723–1727. [PubMed]
48. Prevalence of regular physical activity among adults--United States, 2001 and 2005. MMWR Morb Mortal Wkly Rep. 2007;56:1209–1212. [PubMed]
49. Crespo CJ, Keteyian SJ, Heath GW, Sempos CT. Leisure-time physical activity among US adults. Results from the Third National Health and Nutrition Examination Survey. Arch Intern Med. 1996;156:93–98. [PubMed]
50. Cowie CC, Rust KF, Byrd-Holt DD, Eberhardt MS, Flegal KM, Engelgau MM, Saydah SH, Williams DE, Geiss LS, Gregg EW. Prevalence of diabetes and impaired fasting glucose in adults in the U.S. population: National Health And Nutrition Examination Survey 1999-2002. Diabetes Care. 2006;29:1263–1268. [PubMed]
51. Batsis JA, Romero-Corral A, Collazo-Clavell ML, Sarr MG, Somers VK, Brekke L, Lopez-Jimenez F. Effect of weight loss on predicted cardiovascular risk: change in cardiac risk after bariatric surgery. Obesity (Silver Spring) 2007;15:772–784. [PubMed]
52. Sjostrom L, Narbro K, Sjostrom CD, Karason K, Larsson B, Wedel H, Lystig T, Sullivan M, Bouchard C, Carlsson B, Bengtsson C, Dahlgren S, Gummesson A, Jacobson P, Karlsson J, Lindroos AK, Lonroth H, Naslund I, Olbers T, Stenlof K, Torgerson J, Agren G, Carlsson LM. Effects of bariatric surgery on mortality in Swedish obese subjects. N Engl J Med. 2007;357:741–752. [PubMed]
53. Ajani UA, Ford ES. Has the risk for coronary heart disease changed among U.S. adults? J Am Coll Cardiol. 2006;48:1177–1182. [PubMed]
54. Eckel R, Barouch W, Ershow A. Report of the National Heart, Lung, and Blood Institute-National Institute of Diabetes and Digestive and Kidney Diseases Working Group on the Pathophysiology of Obesity-Associated Cardiovascular Disease. Circulation. 2002;105:2923–2928. [PubMed]
55. Batsis JA, Sarr MG, Collazo-Clavell ML, Thomas RJ, Romero-Corral A, Somers VK, Lopez-Jimenez F. Cardiovascular risk after bariatric surgery for obesity. Am J Cardiol. 2008;102:930–937. [PMC free article] [PubMed]