Dyslipidemia Prevalence, Treatment, and Control in the Multi-Ethnic St
http://www.100md.com
《循环学杂志》
the Department of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC (D.C.G., A.G.B., D.B.)
Department of Preventive Medicine, Loyola Medical Center, Maywood, Ill (H.K.)
Division of Cardiology, Johns Hopkins University School of Medicine, Baltimore, Md (R.S.B.)
Laboratory Medicine and Pathology, University of Minnesota, Minneapolis (M.Y.T.)
Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services, University of Washington, Seattle (B.M.P.).
Abstract
Background— To assess the implementation challenge facing the Third Report of the Adult Treatment Panel (ATP III) of the National Cholesterol Education Program, we determined the prevalence, treatment, and control of dyslipidemia, including ethnic and gender differences, in persons free of known clinical cardiovascular disease (CVD). In addition, this report provides information about the presence of coronary artery calcium (CAC) across groups defined by risk and recommendations for the use of lipid-lowering drugs.
Methods and Results— The Multi-Ethnic Study of Atherosclerosis (MESA) is a multicenter cohort study of 6814 persons aged 45 to 84 years who were free of clinical CVD at baseline (2000–2002). Participants with complete fasting lipid profiles (n=6704) were evaluated for CVD risk and self-reported use of lipid-lowering therapy. CAC was assessed by CT. Drug treatment thresholds and goals were defined according to ATP III. Models were constructed to adjust for age, clinic site, risk factors, socioeconomic characteristics, and healthcare access variables with the use of Poisson regression. Overall, 29.3% (1964/6704) had dyslipidemia, among whom lipid-lowering drug therapy was reported by 54.0% (1060/1964). Control to ATP III goal was observed in 75.2% (797/1060) of participants with treated dyslipidemia and 40.6% (797/1964) of participants with dyslipidemia. Men were more likely than women to qualify for drug therapy and less likely to be treated and controlled. Relative to non-Hispanic whites, Chinese Americans were less likely to qualify for drug treatment, but no differences in treatment and control rates were observed. Black and Hispanic Americans had prevalence of dyslipidemia that was comparable to that of non-Hispanic whites but were less likely to be treated and controlled. Ethnic disparities were attenuated substantially by adjustment for healthcare access variables; however, the gender disparities persisted despite adjustment for risk factors, socioeconomic characteristics, and healthcare access variables. Control of dyslipidemia was achieved less commonly in the CVD high- and intermediate-risk groups than in the low-risk group. Among high-risk individuals, 19.7% of those who did not qualify for lipid-lowering drug treatment had CAC >400. The proportion of drug treatment–qualifying persons who were not treated differed by presence and severity of CAC, with 48.0%, 46.8%, and 39.6% of eligible persons with no CAC, with CAC >0 and <400, and with CAC >400 not receiving treatment, respectively (P for difference=0.04).
Conclusions— Dyslipidemia is common among persons without CVD. The quality of care for dyslipidemia is suboptimal in general and variable by CVD risk group, ethnicity, and gender. The utility of incorporating CAC screening into the risk stratification and treatment process should be investigated in light of the substantial proportions of persons with CAC who are currently classified as not requiring treatment. Research and quality improvement programs are needed to optimize management of dyslipidemia.
Key Words: health services accessibility hypercholesterolemia practice guidelines prevention quality of health care
Introduction
Dyslipidemia is a major risk factor for coronary heart disease, the leading cause of death in the United States.1 Treatment of dyslipidemia can reduce the risk of heart disease by &30% over a 5-year period.2 Although the benefits of lipid-lowering therapy have been demonstrated most conclusively in persons with cardiovascular disease, lipid-lowering therapy is effective even in persons without clinically apparent cardiovascular disease.2 The National Cholesterol Education Program’s series of Adult Treatment Panel (ATP) reports have been developed to provide healthcare professionals with recommendations pertinent to detecting and managing dyslipidemia. The third report, ATP III, was released in May 2001.3 Previous studies have documented the challenges involved in implementing earlier versions of these guidelines in practice settings.4–20 This report describes the prevalence, treatment, and control of dyslipidemia as well as risk group, gender, and ethnic disparities in a cohort of healthy participants at the time ATP III was released. The primary goal of this report is to provide insight into the scope of the challenge facing implementation of ATP III. In addition, this report provides information about the presence of coronary artery calcium (CAC) across groups defined by risk and recommendations for the use of lipid-lowering drugs.
Editorial p 598
Clinical Perspective p 656
Methods
Study Population
The Multi-Ethnic Study of Atherosclerosis (MESA) is a population-based study of 6814 men and women aged 45 to 84 years, without clinical cardiovascular disease, recruited from 6 US communities (Baltimore, Md; Chicago, Ill; Forsyth County, North Carolina; Los Angeles County, California; northern Manhattan, New York; and St Paul, Minn). The main objective of the MESA Study is to determine the characteristics of subclinical cardiovascular disease and its progression. Sampling and recruitment procedures have been previously described in detail and were designed to provide population-based samples.21 Subjects with symptoms or history of medical or surgical treatment for cardiovascular disease were excluded. During the recruitment process, potential participants were asked about their race/ethnicity. Questions on race/ethnicity were based on the US 2000 census questionnaire. Subjects who self-reported their race/ethnicity group as white or Caucasian, black or African American, Chinese, or Spanish/Hispanic/Latino were asked to participate. Race/ethnicity was then categorized as white (non-Hispanic), black (non-Hispanic), Chinese, and Hispanic. Subjects were enrolled between August 1, 2000, and July 30, 2002. Institutional review board approval was obtained at all MESA sites.
Data Collection
All MESA subjects completed self-administered questionnaires and were interviewed by trained research staff to collect information pertaining to demographic characteristics, medical history, medication, and alcohol and tobacco use. These self-administered questionnaires were available in English, Spanish, and Chinese. Trained and certified clinic staff obtained blood samples and anthropometric and blood pressure measurements on all MESA participants during the baseline visit. Height was measured to the nearest 0.1 cm with the subject in stocking feet, and weight was measured to the nearest pound with the subject in light clothing with the use of a balanced scale. Body mass index was calculated as weight in kilograms divided by height in meters squared. After a 5-minute rest, blood pressure was measured 3 times at 1-minute intervals with a Dinamap PRO 100 automated oscillometric device (Critikon) with the subject in a seated position with the back and arm supported.22 The average of the second and third blood pressure measurements was used for this analysis. Hypertension was defined as self-reported treatment for hypertension with 1 of 6 common classes of antihypertensive medications (thiazide diuretics, -blockers, calcium channel blockers, angiotensin-converting enzyme inhibitors, angiotensin type 2 receptor blockers, and other [-blockers or peripheral vasodilators]) or a systolic blood pressure 140 mm Hg or diastolic blood pressure 90 mm Hg. Current smoking and family history of heart attack were ascertained by questionnaire.
Presence of diabetes mellitus was based on self-reported physician diagnosis, use of insulin or an oral hypoglycemic agent, or a fasting glucose value 126 mg/dL at the MESA baseline examination. Serum glucose was measured on fasting samples by rate reflectance spectrophotometry by thin-film adaptation of the glucose oxidase method on a Vitros analyzer (Johnson & Johnson Clinical Diagnostics, Inc) at the Collaborative Studies Clinical Laboratory at Fairview–University Medical Center (Minneapolis, Minn). The laboratory coefficient of variation (CV) was 1.1%.
Information on socioeconomic factors including highest degree or level of school completed, employment status, total household income, residential status, health insurance coverage, and source of usual medical care was collected from the MESA participants by questionnaires. Education was classified into 1 of the following 8 categories: no schooling, grades 1 to 8, grades 9 to 11, completed high school, some college but no degree, technical school certificate, associate degree, bachelor’s degree, and graduate or professional school. Employment status was classified into 1 of the following categories: homemaker, employed full time, employed part time, employed on leave, unemployed, or retired. The total household income included money from jobs; net income from business, farm, or rent; pensions; dividends; welfare; Social Security payments; and any other income received by the participant and all household members living with the participant. Participants were instructed to choose 1 of 13 income categories that best represented the total family income for the past 12 months. Household income was classified as <$5000; $5000 to $7999; $8000 to $11 999; $12 000 to $15 999; $16 000 to $19 999; $20 000 to $24 999; $25 000 to $29 999; $30 000 to $34 999; $35 000 to $39 999; $40 000 to $49 999; $50 000 to $74 999; $75 000 to $99 999; and $100 000. Household size was defined as the number of people living in the household and supported by the household income, including children. Residential status was classified into 1 of the following categories: renting, paying mortgage, own, or other. Health insurance status was also ascertained (private health insurance, HMO, Medicaid, Medicare, veteran’s healthcare, or none). Usual source of routine medical care was classified as a physician’s office or clinic, a hospital or emergency department, or other.
Blood lipids and lipoproteins were measured on samples obtained after an overnight fast. Total cholesterol was measured in EDTA plasma by the cholesterol oxidase method (Roche Diagnostics) on a Roche COBAS FARA centrifugal analyzer at the Collaborative Studies Clinical Laboratory at Fairview–University Medical Center (Minneapolis, Minn). The laboratory CV was 1.6%. HDL cholesterol was measured in EDTA plasma by the cholesterol oxidase method (Roche Diagnostics) after precipitation of non–HDL cholesterol with magnesium/dextran. The laboratory CV was 2.9%. Triglyceride was measured in EDTA plasma with the use of triglyceride GB reagent (Roche Diagnostics) on the Roche COBAS FARA centrifugal analyzer. The laboratory CV was 4.0%. LDL cholesterol was calculated in plasma specimens having a triglyceride value <400 mg/dL by the formula of Friedewald et al.23 Persons with triglyceride values 400 mg/dL were excluded from this analysis. Treatment with lipid-lowering medication was assessed by self-report and included use of statins, fibrate, niacin, and bile acid resins.
Ten-year risk of coronary heart disease was calculated with the use of the Framingham risk score.24 Participants were assigned to 1 of 4 risk categories on the basis of the recommendations provided in ATP III. The 4 risk categories were as follows: (1) low risk, defined as 0 to 1 risk factor for coronary heart disease and a 10-year risk of coronary heart disease <10%; (2) intermediate low risk, defined as 2 risk factors and a 10-year risk of <10%; (3) intermediate high risk, defined as 2 risk factors and a 10-year risk of 10% to 20%; and (4) high risk, defined as coronary heart disease risk equivalent, with a 10-year risk >20%. Participants who were not taking lipid-lowering medications were classified as having dyslipidemia if their LDL cholesterol concentration exceeded the risk group–specific threshold recommended in ATP III for consideration of drug therapy: 190, 160, 130, and 130 mg/dL for risk groups 1 through 4, respectively. All participants treated with lipid-lowering drugs were classified as having dyslipidemia. Consequently, persons with prevalent dyslipidemia include all participants who were treated with a lipid-lowering drug and those who qualified for treatment but were not treated. Control of dyslipidemia was defined as an observed LDL cholesterol <160, 130, 130, and 100 mg/dL for risk groups 1 through 4, respectively. In analyses of control, the 2 intermediate groups were collapsed into a single group to maintain sample size because those 2 groups share a common treatment goal. Given our definition of dyslipidemia and lack of information on use of lifestyle therapy, only drug-treated persons could be controlled.
Chest CT was performed by either a cardiac-gated electron-beam CT scanner25 or a prospective ECG-triggered scan acquisition at 50% of the R-R interval with a multidetector CT system26 acquiring a block of four 2.5-mm slices for each cardiac cycle in a sequential or axial scan mode. All participants were scanned over phantoms of known physical calcium concentration. Scans were read centrally at the Harbor-UCLA Research and Education Institute in Torrance, Calif, to identify and quantify coronary calcification, calibrated according to the readings of the calcium phantom. The average Agatston score was used in all analyses.27
Statistical Analysis
All analyses were performed with the use of Stata, version 8.0 (Stata Corporation). Means, SDs, and proportions were used to summarize the characteristics of the study sample. Continuous variables were compared by ANOVA, and categorical variables were compared by the 2 statistic. When gender and ethnic groups were compared, ANOVA was used to assess racial differences of continuous variables among the 8 gender-ethnic groups.
Multivariable Poisson regression was used to examine the association between risk group, gender, and ethnicity and dyslipidemia in the MESA population. Several different sets of models were constructed to examine each outcome of interest: dyslipidemia prevalence, treatment, and control. For each outcome, 3 models were examined so that changes in the parameter estimate with the addition of risk factors and socioeconomic factors could be examined. Model 1 adjusted for age and clinical site and included gender and ethnicity. Model 2 added risk factors (body mass index, hypertension, diabetes, current smoking, and family history of heart attack). Model 3 added socioeconomic (education, employment status, income, household size, residential status) and healthcare access (source of usual medical care and health insurance coverage) variables to model 2.
The presence and severity of CAC across groups defined by risk and treatment recommendations were examined by ordered logistic regression with outcome categories of CAC <0, CAC >0 and <400, and CAC 400. The assumption of homogeneity of odds ratios across thresholds of CAC was tested and met.
Results
A total of 6814 men and women (38% non-Hispanic white, 28% black, 12% Chinese, 22% Hispanic) between the ages of 45 and 84 years completed the first MESA examination. Non-Hispanic whites were recruited at all 6 sites, blacks were recruited at 5 of 6 sites (not St Paul), Chinese were recruited predominantly in Chicago and Los Angeles, and Hispanics were recruited primarily in northern Manhattan, St Paul, and Los Angeles. The majority of both non-Hispanic whites and blacks reported being born in the United States or Puerto Rico (>90%); 96% of Chinese and 58% of Hispanic subjects reported being born outside the United States. Among the Hispanics born outside the United States or Puerto Rico, birthplace was reported as Mexico in 43%, Dominican Republic in 20%, South America in 15%, Central America in 7%, and other countries in 15%. The characteristics of the 6704 MESA participants with complete data on lipid and lipoprotein concentrations are shown in Table 1.
Observed lipid and lipoprotein cholesterol concentrations are provided in Table 2; all measures differed significantly by gender-ethnic group (P<0.001). The overall observed total cholesterol concentration was 193.5 mg/dL. The lowest concentrations were observed in black men (181.4 mg/dL), and the highest concentrations were observed in non-Hispanic white women (201.3 mg/dL). LDL cholesterol concentrations ranged from 113.5 mg/dL in black men to 119.6 mg/dL in Hispanic women, with an overall average of 117.2 mg/dL.
Descriptive results with regard to 10-year risk of coronary heart disease, dyslipidemia prevalence, treatment, and control are shown in Table 3; all measures differed significantly by gender-ethnic group (P<0.001). The 10-year risk of coronary heart disease differed primarily by gender and ranged from 3.8% in non-Hispanic white women to 13.4% in black men. The prevalence of dyslipidemia was 29.3% overall and ranged from 21.0% in Chinese women to 36.9% in non-Hispanic white men. Lipid-lowering drug therapy was reported by 15.8% of MESA participants, ranging from 12.5% in Chinese men to 19.2% in non-Hispanic white men; 54.0% of persons with dyslipidemia reported lipid-lowering drug treatment, ranging from 39.4% in Hispanic men to 74.1% of Chinese women.
In the total MESA population, LDL cholesterol concentrations were below the ATP III–defined drug treatment initiation threshold for 85.0%, ranging from 78.5% of Hispanic men to 93.3% of Chinese women, and LDL cholesterol concentrations were below the ATP III–defined drug treatment goal for 67.4%, ranging from 58.6% of Hispanic men to 79.5% of Chinese women. Of persons with dyslipidemia, only 40.6% were controlled to goal, ranging from 27.0% of Hispanic men to 61.2% of Chinese women; 75.3% of persons with treated dyslipidemia were controlled to goal, ranging from 65.7% of black women to 86.2% of non-Hispanic white women.
Age-specific results with regard to dyslipidemia prevalence, treatment, and control are provided in Table 4. The general pattern is consistent with a greater prevalence of dyslipidemia in the older age groups, a finding that is significant (P<0.001) after adjustment for gender, ethnicity, clinic site, risk factors, and socioeconomic and healthcare access variables. This general pattern was observed across gender and ethnic groups. Prevalence of treatment was greater in the older age groups, at least until age 75 years; however, this finding was not significant after adjustment for risk factors and socioeconomic and healthcare access variables. No difference was observed across age groups in control among persons with treated dyslipidemia.
Prevalence ratios (and corresponding 95% CIs) comparing gender and ethnic groups with respect to dyslipidemia prevalence, treatment, and control are shown in Table 5. In regard to gender comparisons, men were &30% more likely than women to have dyslipidemia; adjustment for risk factors and socioeconomic and healthcare access variables had no substantive effect on these findings. Men were &20% less likely than women to report drug treatment among the subset with dyslipidemia. Adjustment for risk factors and socioeconomic and healthcare access variables had no substantive effect on findings related to treatment of dyslipidemia. Among persons with dyslipidemia, men were &30% less likely than women to have their dyslipidemia controlled; in the treated subgroup, men were &10% less likely to be controlled. Among all MESA participants, men were &15% less likely than women to have their dyslipidemia controlled. Adjustment for risk factors and socioeconomic and healthcare access variables had no substantive effect on findings related to control of dyslipidemia.
With regard to ethnic comparisons, Chinese participants were 20% less likely than non-Hispanic whites to have dyslipidemia, and this difference was somewhat attenuated by adjustment for risk factors and socioeconomic and healthcare access variables. No difference was observed between blacks, Hispanics, and non-Hispanic whites. Hispanics were &20% and blacks were &15% less likely than non-Hispanic whites to report drug treatment. This difference was substantially attenuated by adjustment for socioeconomic and healthcare access variables for Hispanics. No significant differences were observed in drug treatment between Chinese and non-Hispanic white participants with dyslipidemia. Among participants with dyslipidemia (whether treated or not), blacks and Hispanics were &30% less likely than non-Hispanic whites to have their dyslipidemia controlled; in the treated subgroup, blacks and Hispanics were 16% and 6% (P=NS) less likely to be controlled. Adjustment for socioeconomic and healthcare access variables attenuated these findings substantially. Among all MESA participants, ethnic differences in prevalence of dyslipidemia control were <10%; however, these relatively small disparities were significant when blacks were compared with non-Hispanic whites. Adjustment for risk factors and socioeconomic and healthcare access variables attenuated these relationships substantially.
When classified into ATP II risk categories, 34.8% (2330/6704) of MESA participants were low risk, 43.6% (2925/6704) were intermediate risk, and 21.6% (1449/6704) were high risk (coronary heart disease risk equivalent). The prevalence of dyslipidemia was 11.7%, 33.6%, and 48.9% across these categories (P<0.001). Dyslipidemia treatment and control status is shown by ATP III risk category in Figure 1. Few low-risk participants qualified for dyslipidemia solely on the basis of high untreated LDL cholesterol concentrations. More than 80% of the low-risk group was treated, whereas only half of the intermediate- and high-risk groups were treated (P<0.001). Almost all treated low-risk participants were controlled versus &80% of treated intermediate-risk participants and half of treated high-risk participants (P<0.001). Dyslipidemia control is shown by gender, ethnicity, and ATP III risk category in Figure 2. The difference in control across ATP III risk categories is present across gender and ethnic groups.
The distribution of CAC score by ATP III risk-based treatment category is shown in Table 6. The presence and severity of CAC were greater in persons who met criteria for intermediate and high risk and in persons who met criteria for lipid-lowering drug treatment; however, the high-risk group that did not meet criteria for drug treatment had greater prevalence and severity of CAC than either of the lower-risk groups that did meet criteria for lipid-lowering drug treatment. These results were confirmed after adjustment for age, gender, ethnicity, and clinic site. Persons who met ATP III criteria for lipid-lowering drug treatment had an odds ratio for greater prevalence and severity of CAC of 1.59 (95% CI, 1.42 to 1.78; P<0.001). In comparison with low-risk individuals, intermediate- and high-risk participants had odds ratios of 1.67 (95% CI, 1.47 to 1.88; P<0.001) and 2.12 (95% CI, 1.82 to 2.47; P<0.001), respectively. The interaction of risk and treatment categories was examined and was not significant (P=0.31). Overall, 46.0% of lipid-lowering drug treatment–eligible participants were not receiving treatment. The proportion not treated differed by presence and severity of CAC, with 48.0%, 46.8%, and 39.6% of eligible persons with no CAC, with CAC >0 and <400, and with CAC 400 not receiving treatment, respectively (P for difference=0.04).
Discussion
In this middle-aged and older multiethnic cohort of people free of clinical cardiovascular disease, the prevalence of drug treatment–eligible dyslipidemia, as defined in ATP III, was &29%. Overall, 16% of the population reported treatment with lipid-lowering drugs, including 54% of those with dyslipidemia. Dyslipidemia was more common in men than in women and was treated and controlled less often in men than in women. Dyslipidemia prevalence differed little across ethnic groups, with the exception of a lower prevalence in Chinese subjects. Drug treatment also differed little across ethnic groups, with the exception of a lower prevalence of treatment reported by Hispanic subjects. Among persons with dyslipidemia, control of dyslipidemia was achieved less commonly in blacks and Hispanics than in non-Hispanic whites. Control of dyslipidemia was achieved less commonly in high-risk and intermediate-risk than in low-risk individuals. These results support several conclusions. Dyslipidemia, as defined by ATP III, is common in a population free of known clinical cardiovascular disease. Dyslipidemia treatment and control is far from optimal. The highest risk group has the lowest level of control, and there is evidence of gender and ethnic disparities in both treatment and control.
The findings related to gender disparities may reflect, at least in part, the combined effects of gender differences in risk-based thresholds for the definition of dyslipidemia, healthcare-seeking behaviors, and access to healthcare. Because male gender is recognized to increase the risk of coronary heart disease by the Framingham risk score, even if total and LDL cholesterol concentrations are equal in men and women, men will have cholesterol concentrations that more often cross the treatment threshold. Furthermore, men will more often meet criteria for a lower treatment goal. Women are more likely than men to have both health insurance and an ongoing source for primary care28 and are reported to seek healthcare services more often than men.29 These behavioral differences could explain part of the observed gender differences in treatment and control. Adjustment for healthcare access did not attenuate our findings; however, our measures of access did not include a measure of healthcare-seeking behavior.
Ethnic differences in prevalence of dyslipidemia were observed only for Chinese subjects, who had the lowest prevalence of dyslipidemia. This difference could be related to dietary and other cultural differences that result in lower total and LDL cholesterol concentrations.30 Chinese subjects were also less likely to report a family history of heart attack or, at least among women, current cigarette smoking. These risk factor differences could lead to the classification of a greater proportion of Chinese (than non-Hispanic whites) into a lower-risk group, with correspondingly higher treatment initiation and goal thresholds.
The observed ethnic disparities in treatment and control, with the relative deficits observed in blacks and Hispanics, are potentially due to ethnic differences in healthcare-seeking behaviors and access to care. Black and Hispanic Americans are well known to have lower insurance coverage rates and poorer access to care, as exemplified by greater reliance on emergency departments for healthcare services.29 This contention is supported by the results of analyses performed to examine whether the observed differences in dyslipidemia prevalence, treatment, and control could be attributed to differences in risk factors for coronary heart disease, socioeconomic characteristics, and healthcare access variables. Ethnic differences in treatment were attenuated more by adjustment for socioeconomic characteristics and healthcare access variables than by adjustment for other risk factors. Ethnic differences in control were attenuated by adjustment for both risk factors and socioeconomic and healthcare access variables. These patterns were especially apparent among Hispanics. These observations support the speculation that the ethnic disparity in treatment relates to differences in access to care, and the ethnic differences in control relate to differences in both access to care and the risk-specific treatment thresholds. The relative absence of ethnic disparities in control among persons with treated dyslipidemia supports the conclusion that the medications, when used, may be equally effective across ethnic groups. In contrast, neither sets of variables accounted for an appreciable proportion of the observed gender differences, suggesting that other factors underlie the observed gender differences.
The results of analyses of presence and severity of CAC by ATP III risk-based treatment group support the conclusion that the risk estimation process incorporated into ATP III distinguishes between groups that differ with respect to CAC. However, the discrimination was far from perfect. In addition, the magnitude of undertreatment observed in MESA differed minimally by presence and severity of CAC. This observation is not surprising because CAC was measured after the lipid-lowering treatment status had been determined; hence, the participants’ healthcare providers had no knowledge of the CAC scores when making treatment recommendations. These findings support the speculation that the providers were not very effective at targeting treatment to the highest-risk patients, at least insofar as presence and severity of CAC correlate with risk. Although CAC has been shown to predict risk of cardiovascular events,31 CAC-guided treatment has not been demonstrated to reduce progression of CAC32,33 or event rates, although little relevant research has been conducted to date. To the extent that the presence and severity of CAC might improve the ability to predict who might benefit from lipid-lowering drug treatment, the discriminatory ability of the ATP III risk-based algorithm might be enhanced considerably by information about CAC. Additional research is needed to investigate this possibility, including trials in persons with CAC who do not otherwise meet current criteria for lipid-lowering therapy. The urgency of this research is underscored by the observation that many drug-eligible persons with substantial CAC were not treated and many persons who did not qualify for drug treatment had substantial CAC.
This study is limited by the exclusion of persons with clinical cardiovascular disease, and therefore we cannot address secondary prevention. In addition, the study population was limited to 4 ethnic groups and 6 geographic areas in the United States; hence, these results may not be representative of other ethnic groups or of nationally representative patterns. The recruitment process was designed to produce a study population that was representative of residents without clinical cardiovascular disease; however, it is possible that participants were more health conscious than nonparticipants. The likely effect of this potential bias could be to lead to an underestimation of dyslipidemia prevalence and overestimation of treatment and control rates. Gender, ethnicity, and risk group comparisons could be biased if the magnitude of this potential selection bias differed by 1 or more of these characteristics. Finally, data collection spanned a period that included time before the release of ATP III; hence, these results should be interpreted as describing the scope of the challenge facing implementation of the ATP III guidelines rather than as evidence about the relative success or failure of implementation efforts. The challenge is greatest for the highest-risk group, among which three quarters were not controlled, but was substantial among the intermediate-risk group, among which three fifths were not controlled. This pattern of lesser control at higher risk is due, to a substantial extent, to the lower LDL cholesterol goal applied to the higher-risk groups. Quilliam et al34 provided insight into this challenge in an analysis of data from a managed care population. Among patients treated with HMG-CoA reductase inhibitors in early 2001, control to LDL cholesterol goals was 59.8% when ATP II guidelines were used and 53.0% when ATP III guidelines were used.34 We observed control rates that differed markedly by risk group among treated participants, from almost all treated low-risk persons to approximately half of the treated high-risk persons. This pattern is consistent with results from the Lipid Treatment Assessment Project (L-TAP) study that showed control rates of 68%, 37%, and 18% among low-risk, high-risk, and coronary heart disease patients, respectively, based on ATP II criteria, although our results showed higher control rates across risk groups than were observed in the L-TAP population in 1996–1997.7 Although additional research will be required to evaluate progress toward the goal of implementation, it is clear that the public health challenge posed by cholesterol control is substantial. According to the ATP III report, &16 million US adults without coronary heart disease qualify for lipid-lowering drug treatment.3 If our results are applied to this estimate, 7.4 million adults in the United States need lipid-lowering therapy initiated, and another 2.3 million adults need intensification of therapy to meet ATP III goals.
These results support several conclusions. Dyslipidemia requiring drug treatment is common in the middle-aged and older adult population of the United States among persons with no evidence of clinical cardiovascular disease. Rates of treatment and control of dyslipidemia are far from optimal, especially among the intermediate- and high-risk groups, and provide evidence of gender- and ethnicity-related disparities. The utility of incorporating CAC screening into the risk stratification and treatment process should be investigated in light of the substantial proportions of persons with CAC who are currently classified as not requiring treatment. Undertreatment of persons with dyslipidemia is a major public health challenge. Given the significance of cardiovascular disease as a public health problem in the United States and the proven benefits of lipid-lowering therapy for primary prevention, efforts to improve the treatment and control of dyslipidemia and to eliminate disparities in dyslipidemia management should be considered among our highest national healthcare quality improvement priorities.
Acknowledgments
This research was supported by contracts N01-HC-95159 through N01-HC-95165 and N01-HC-95166 from the National Heart, Lung, and Blood Institute. Staff scientists from the National Heart, Lung, and Blood Institute were involved in the design and conduct of the study, the oversight of the data collection, management, and analysis processes, and the review and approval of this article. The authors thank the other investigators, the staff, and the participants of the MESA Study for their valuable contributions. A full list of participating MESA investigators and institutions can be found at http://www.mesa-nhlbi.org.
Disclosures
Dr Goff reports having received speaker’s honoraria from Pfizer (<$10 000) and having served on the Preventive Cardiology Advisory Board of Pfizer (<$10 000). Dr Blumenthal reports having served on the speaker’s bureaus of Pfizer, Merck, KOS, Astra-Zeneca, and Schering-Plough (all <$10 000) and having received speaker’s honoraria from Pfizer, Merck, KOS, Astra-Zeneca, and Schering-Plough (all <$10 000). The remaining authors report no conflicts of interest.
References
American Heart Association. Heart Disease and Stroke Statistics—2004 Update. Dallas, Tex: American Heart Association; 2003.
Grundy SM, Cleeman JI, Merz CN, Brewer HB Jr, Clark LT, Hunninghake DB, Pasternak RC, Smith SC Jr, Stone NJ. Implications of recent clinical trials for the National Cholesterol Education Program Adult Treatment Panel III guidelines. J Am Coll Cardiol. 2004; 44: 720–732.
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): final report. Circulation. 2002; 106: 3143–3421.
Goff DC Jr, Gu L, Cantley LK, Parker DG, Cohen SJ. Enhancing the quality of care for patients with coronary heart disease: the design and baseline results of the Hastening the Effective Application of Research Through Technology (HEART) trial. Am J Manag Care. 2002; 8: 1069–1078.
Goff DC Jr, Gu L, Cantley LK, Sheedy DJ, Cohen SJ. Quality of care for secondary prevention for patients with coronary heart disease: results of the Hastening the Effective Application of Research Through Technology (HEART) trial. Am Heart J. 2003; 146: 1045–1051.
Banks T, Ali N. Coronary care physician 1994–2000 adherence to 1993 National Cholesterol Education Program diet and lipid recommendations. J Natl Med Assoc. 2001; 93: 87–91.
Pearson TA, Laurora I, Chu H, Kafonek S. The Lipid Treatment Assessment Project (L-TAP): a multicenter survey to evaluate the percentages of dyslipidemic patients receiving lipid-lowering therapy and achieving low-density lipoprotein cholesterol goals. Arch Intern Med. 2000; 160: 459–467.
Stafford RS, Blumenthal D, Pasternak RC. Variations in cholesterol management practices of U.S. physicians. J Am Coll Cardiol. 1997; 29: 139–146.
Sueta CA, Chowdhury M, Boccuzzi SJ, Smith SC Jr, Alexander CM, Londhe A, Lulla A, Simpson RJ Jr. Analysis of the degree of undertreatment of hyperlipidemia and congestive heart failure secondary to coronary artery disease. Am J Cardiol. 1999; 83: 1303–1307.
Smith SC Jr. Clinical treatment of dyslipidemia: practice patterns and missed opportunities. Am J Cardiol. 2000; 86: 62L–65L.
McBride P, Schrott HG, Plane MB, Underbakke G, Brown RL. Primary care practice adherence to National Cholesterol Education Program guidelines for patients with coronary heart disease. Arch Intern Med. 1998; 158: 1238–1244.
Bramlet DA, King H, Young L, Witt JR, Stoukides CA, Kaul AF. Management of hypercholesterolemia: practice patterns for primary care providers and cardiologists. Am J Cardiol. 1997; 80: 39H–44H.
Nieto FJ, Alonso J, Chambless LE, Zhong M, Ceraso M, Romm FJ, Cooper L, Folsom AR, Szklo M. Population awareness and control of hypertension and hypercholesterolemia: the Atherosclerosis Risk in Communities Study. Arch Intern Med. 1995; 155: 677–684.
The Clinical Quality Improvement Network (CQIN) Investigators. Low incidence of assessment and modification of risk factors in acute care patients at high risk for cardiovascular events, particularly among females and the elderly. Am J Cardiol. 1995; 76: 570–573.
Giles WH, Anda RF, Jones DH, Serdula MK, Merritt RK, DeStefano F. Recent trends in the identification and treatment of high blood cholesterol by physicians: progress and missed opportunities. JAMA. 1993; 269: 1133–1138.
Cohen MV, Byrne MJ, Levine B, Gutowski T, Adelson R. Low rate of treatment of hypercholesterolemia by cardiologists in patients with suspected and proven coronary artery disease. Circulation. 1991; 83: 1294–1304.
Hoerger TJ, Bala MV, Bray JW, Wilcosky TC, LaRosa J. Treatment patterns and distribution of low-density lipoprotein cholesterol levels in treatment-eligible United States adults. Am J Cardiol. 1998; 82: 61–65.
Straka RJ, Taheri R, Cooper SL, Tan AW, Smith AC. Assessment of hypercholesterolemia control in a managed care organization. Pharmacotherapy. 2001; 21: 818–827.
Abookire SA, Karson AS, Fiskio J, Bates DW. Use and monitoring of "statin" lipid-lowering drugs compared with guidelines. Arch Intern Med. 2001; 161: 53–58.
Massing MW, Foley KA, Carter-Edwards L, Sueta CA, Alexander CM, Simpson RJ Jr. Disparities in lipid management for African Americans and Caucasians with coronary artery disease: a national cross-sectional study. BMC Cardiovasc Disord. 2004; 4: 15.
Bild DE, Bluemke DA, Burke GL, Detrano R, Diez Roux AV, Folsom AR, Greenland P, Jacob DR Jr, Kronmal R, Liu K, Nelson JC, O’Leary D, Saad MF, Shea S, Szklo M, Tracy RP. Multi-ethnic study of atherosclerosis: objectives and design. Am J Epidemiol. 2002; 156: 871–881.
Chang JJ, Rabinowitz D, Shea S. Sources of variability in blood pressure measurement using the Dinamap PRO 100 automated oscillometric device. Am J Epidemiol. 2003; 158: 1218–1226.
Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem. 1972; 18: 499–502.
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.
Breen JF, Sheedy PF, Schwartz RS, Stanson AW, Kaufmann RB, Moll PP, Rumberger JA. Coronary artery calcification detected with ultrafast CT as an indication of coronary artery disease. Radiology. 1992; 185: 435–439.
Carr JJ, Crouse JR III, Goff DC Jr, D’Agostino RB Jr, Peterson NP, Burke GL. Evaluation of subsecond gated helical CT for quantification of coronary artery calcium and comparison with electron beam CT. AJR Am J Roentgenol. 2000; 174: 915–921.
Agatston AS, Janowitz WR, Hildner FJ, Zusmer NR, Viamonte M Jr, Detrano R. Quantification of coronary artery calcium using ultrafast computed tomography. J Am Coll Cardiol. 1990; 15: 827–832.
Maiese DR. Healthy people 2010: leading health indicators for women. Womens Health Issues. 2002; 12: 155–164.
Lethbridge-Cejku M, Schiller JS, Bernadel L. Summary health statistics for U.S. adults: National Health Interview Survey, 2002. National Center for Health Statistics. Vital Health Stat 10 (222); 2004.
Huang MH, Schocken M, Block G, Sowers M, Gold E, Sternfeld B, Seeman T, Greendale GA. Variation in nutrient intakes by ethnicity: results from the Study of Women’s Health Across the Nation (SWAN). Menopause. 2002; 9: 309–319.
Greenland P, LaBree L, Azen SP, Doherty TM, Detrano RC. Coronary artery calcium score combined with Framingham score for risk prediction in asymptomatic individuals. JAMA. 2004; 291: 210–215.
Wong ND, Kawakubo M, LaBree L, Azen SP, Xiang M, Detrano R. Relation of coronary calcium progression and control of lipids according to National Cholesterol Education Program guidelines. Am J Cardiol. 2004; 94: 431–436.
Raggi P, Davidson M, Callister TQ, Welty FK, Bachmann GA, Hecht H, Rumberger JA. Aggressive versus moderate lipid-lowering therapy in hypercholesterolemic postmenopausal women: Beyond Endorsed Lipid Lowering with EBT Scanning (BELLES). Circulation. 2005; 112: 563–571.
Quilliam BJ, Perez HE, Andros V, Jones P. Quantifying the effect of applying the NCEP ATP III criteria in a managed care population treated with statin therapy. J Manag Care Pharm. 2004; 10: 244–250.(David C. Goff, Jr, MD, PhD; Alain G. Ber)
Department of Preventive Medicine, Loyola Medical Center, Maywood, Ill (H.K.)
Division of Cardiology, Johns Hopkins University School of Medicine, Baltimore, Md (R.S.B.)
Laboratory Medicine and Pathology, University of Minnesota, Minneapolis (M.Y.T.)
Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services, University of Washington, Seattle (B.M.P.).
Abstract
Background— To assess the implementation challenge facing the Third Report of the Adult Treatment Panel (ATP III) of the National Cholesterol Education Program, we determined the prevalence, treatment, and control of dyslipidemia, including ethnic and gender differences, in persons free of known clinical cardiovascular disease (CVD). In addition, this report provides information about the presence of coronary artery calcium (CAC) across groups defined by risk and recommendations for the use of lipid-lowering drugs.
Methods and Results— The Multi-Ethnic Study of Atherosclerosis (MESA) is a multicenter cohort study of 6814 persons aged 45 to 84 years who were free of clinical CVD at baseline (2000–2002). Participants with complete fasting lipid profiles (n=6704) were evaluated for CVD risk and self-reported use of lipid-lowering therapy. CAC was assessed by CT. Drug treatment thresholds and goals were defined according to ATP III. Models were constructed to adjust for age, clinic site, risk factors, socioeconomic characteristics, and healthcare access variables with the use of Poisson regression. Overall, 29.3% (1964/6704) had dyslipidemia, among whom lipid-lowering drug therapy was reported by 54.0% (1060/1964). Control to ATP III goal was observed in 75.2% (797/1060) of participants with treated dyslipidemia and 40.6% (797/1964) of participants with dyslipidemia. Men were more likely than women to qualify for drug therapy and less likely to be treated and controlled. Relative to non-Hispanic whites, Chinese Americans were less likely to qualify for drug treatment, but no differences in treatment and control rates were observed. Black and Hispanic Americans had prevalence of dyslipidemia that was comparable to that of non-Hispanic whites but were less likely to be treated and controlled. Ethnic disparities were attenuated substantially by adjustment for healthcare access variables; however, the gender disparities persisted despite adjustment for risk factors, socioeconomic characteristics, and healthcare access variables. Control of dyslipidemia was achieved less commonly in the CVD high- and intermediate-risk groups than in the low-risk group. Among high-risk individuals, 19.7% of those who did not qualify for lipid-lowering drug treatment had CAC >400. The proportion of drug treatment–qualifying persons who were not treated differed by presence and severity of CAC, with 48.0%, 46.8%, and 39.6% of eligible persons with no CAC, with CAC >0 and <400, and with CAC >400 not receiving treatment, respectively (P for difference=0.04).
Conclusions— Dyslipidemia is common among persons without CVD. The quality of care for dyslipidemia is suboptimal in general and variable by CVD risk group, ethnicity, and gender. The utility of incorporating CAC screening into the risk stratification and treatment process should be investigated in light of the substantial proportions of persons with CAC who are currently classified as not requiring treatment. Research and quality improvement programs are needed to optimize management of dyslipidemia.
Key Words: health services accessibility hypercholesterolemia practice guidelines prevention quality of health care
Introduction
Dyslipidemia is a major risk factor for coronary heart disease, the leading cause of death in the United States.1 Treatment of dyslipidemia can reduce the risk of heart disease by &30% over a 5-year period.2 Although the benefits of lipid-lowering therapy have been demonstrated most conclusively in persons with cardiovascular disease, lipid-lowering therapy is effective even in persons without clinically apparent cardiovascular disease.2 The National Cholesterol Education Program’s series of Adult Treatment Panel (ATP) reports have been developed to provide healthcare professionals with recommendations pertinent to detecting and managing dyslipidemia. The third report, ATP III, was released in May 2001.3 Previous studies have documented the challenges involved in implementing earlier versions of these guidelines in practice settings.4–20 This report describes the prevalence, treatment, and control of dyslipidemia as well as risk group, gender, and ethnic disparities in a cohort of healthy participants at the time ATP III was released. The primary goal of this report is to provide insight into the scope of the challenge facing implementation of ATP III. In addition, this report provides information about the presence of coronary artery calcium (CAC) across groups defined by risk and recommendations for the use of lipid-lowering drugs.
Editorial p 598
Clinical Perspective p 656
Methods
Study Population
The Multi-Ethnic Study of Atherosclerosis (MESA) is a population-based study of 6814 men and women aged 45 to 84 years, without clinical cardiovascular disease, recruited from 6 US communities (Baltimore, Md; Chicago, Ill; Forsyth County, North Carolina; Los Angeles County, California; northern Manhattan, New York; and St Paul, Minn). The main objective of the MESA Study is to determine the characteristics of subclinical cardiovascular disease and its progression. Sampling and recruitment procedures have been previously described in detail and were designed to provide population-based samples.21 Subjects with symptoms or history of medical or surgical treatment for cardiovascular disease were excluded. During the recruitment process, potential participants were asked about their race/ethnicity. Questions on race/ethnicity were based on the US 2000 census questionnaire. Subjects who self-reported their race/ethnicity group as white or Caucasian, black or African American, Chinese, or Spanish/Hispanic/Latino were asked to participate. Race/ethnicity was then categorized as white (non-Hispanic), black (non-Hispanic), Chinese, and Hispanic. Subjects were enrolled between August 1, 2000, and July 30, 2002. Institutional review board approval was obtained at all MESA sites.
Data Collection
All MESA subjects completed self-administered questionnaires and were interviewed by trained research staff to collect information pertaining to demographic characteristics, medical history, medication, and alcohol and tobacco use. These self-administered questionnaires were available in English, Spanish, and Chinese. Trained and certified clinic staff obtained blood samples and anthropometric and blood pressure measurements on all MESA participants during the baseline visit. Height was measured to the nearest 0.1 cm with the subject in stocking feet, and weight was measured to the nearest pound with the subject in light clothing with the use of a balanced scale. Body mass index was calculated as weight in kilograms divided by height in meters squared. After a 5-minute rest, blood pressure was measured 3 times at 1-minute intervals with a Dinamap PRO 100 automated oscillometric device (Critikon) with the subject in a seated position with the back and arm supported.22 The average of the second and third blood pressure measurements was used for this analysis. Hypertension was defined as self-reported treatment for hypertension with 1 of 6 common classes of antihypertensive medications (thiazide diuretics, -blockers, calcium channel blockers, angiotensin-converting enzyme inhibitors, angiotensin type 2 receptor blockers, and other [-blockers or peripheral vasodilators]) or a systolic blood pressure 140 mm Hg or diastolic blood pressure 90 mm Hg. Current smoking and family history of heart attack were ascertained by questionnaire.
Presence of diabetes mellitus was based on self-reported physician diagnosis, use of insulin or an oral hypoglycemic agent, or a fasting glucose value 126 mg/dL at the MESA baseline examination. Serum glucose was measured on fasting samples by rate reflectance spectrophotometry by thin-film adaptation of the glucose oxidase method on a Vitros analyzer (Johnson & Johnson Clinical Diagnostics, Inc) at the Collaborative Studies Clinical Laboratory at Fairview–University Medical Center (Minneapolis, Minn). The laboratory coefficient of variation (CV) was 1.1%.
Information on socioeconomic factors including highest degree or level of school completed, employment status, total household income, residential status, health insurance coverage, and source of usual medical care was collected from the MESA participants by questionnaires. Education was classified into 1 of the following 8 categories: no schooling, grades 1 to 8, grades 9 to 11, completed high school, some college but no degree, technical school certificate, associate degree, bachelor’s degree, and graduate or professional school. Employment status was classified into 1 of the following categories: homemaker, employed full time, employed part time, employed on leave, unemployed, or retired. The total household income included money from jobs; net income from business, farm, or rent; pensions; dividends; welfare; Social Security payments; and any other income received by the participant and all household members living with the participant. Participants were instructed to choose 1 of 13 income categories that best represented the total family income for the past 12 months. Household income was classified as <$5000; $5000 to $7999; $8000 to $11 999; $12 000 to $15 999; $16 000 to $19 999; $20 000 to $24 999; $25 000 to $29 999; $30 000 to $34 999; $35 000 to $39 999; $40 000 to $49 999; $50 000 to $74 999; $75 000 to $99 999; and $100 000. Household size was defined as the number of people living in the household and supported by the household income, including children. Residential status was classified into 1 of the following categories: renting, paying mortgage, own, or other. Health insurance status was also ascertained (private health insurance, HMO, Medicaid, Medicare, veteran’s healthcare, or none). Usual source of routine medical care was classified as a physician’s office or clinic, a hospital or emergency department, or other.
Blood lipids and lipoproteins were measured on samples obtained after an overnight fast. Total cholesterol was measured in EDTA plasma by the cholesterol oxidase method (Roche Diagnostics) on a Roche COBAS FARA centrifugal analyzer at the Collaborative Studies Clinical Laboratory at Fairview–University Medical Center (Minneapolis, Minn). The laboratory CV was 1.6%. HDL cholesterol was measured in EDTA plasma by the cholesterol oxidase method (Roche Diagnostics) after precipitation of non–HDL cholesterol with magnesium/dextran. The laboratory CV was 2.9%. Triglyceride was measured in EDTA plasma with the use of triglyceride GB reagent (Roche Diagnostics) on the Roche COBAS FARA centrifugal analyzer. The laboratory CV was 4.0%. LDL cholesterol was calculated in plasma specimens having a triglyceride value <400 mg/dL by the formula of Friedewald et al.23 Persons with triglyceride values 400 mg/dL were excluded from this analysis. Treatment with lipid-lowering medication was assessed by self-report and included use of statins, fibrate, niacin, and bile acid resins.
Ten-year risk of coronary heart disease was calculated with the use of the Framingham risk score.24 Participants were assigned to 1 of 4 risk categories on the basis of the recommendations provided in ATP III. The 4 risk categories were as follows: (1) low risk, defined as 0 to 1 risk factor for coronary heart disease and a 10-year risk of coronary heart disease <10%; (2) intermediate low risk, defined as 2 risk factors and a 10-year risk of <10%; (3) intermediate high risk, defined as 2 risk factors and a 10-year risk of 10% to 20%; and (4) high risk, defined as coronary heart disease risk equivalent, with a 10-year risk >20%. Participants who were not taking lipid-lowering medications were classified as having dyslipidemia if their LDL cholesterol concentration exceeded the risk group–specific threshold recommended in ATP III for consideration of drug therapy: 190, 160, 130, and 130 mg/dL for risk groups 1 through 4, respectively. All participants treated with lipid-lowering drugs were classified as having dyslipidemia. Consequently, persons with prevalent dyslipidemia include all participants who were treated with a lipid-lowering drug and those who qualified for treatment but were not treated. Control of dyslipidemia was defined as an observed LDL cholesterol <160, 130, 130, and 100 mg/dL for risk groups 1 through 4, respectively. In analyses of control, the 2 intermediate groups were collapsed into a single group to maintain sample size because those 2 groups share a common treatment goal. Given our definition of dyslipidemia and lack of information on use of lifestyle therapy, only drug-treated persons could be controlled.
Chest CT was performed by either a cardiac-gated electron-beam CT scanner25 or a prospective ECG-triggered scan acquisition at 50% of the R-R interval with a multidetector CT system26 acquiring a block of four 2.5-mm slices for each cardiac cycle in a sequential or axial scan mode. All participants were scanned over phantoms of known physical calcium concentration. Scans were read centrally at the Harbor-UCLA Research and Education Institute in Torrance, Calif, to identify and quantify coronary calcification, calibrated according to the readings of the calcium phantom. The average Agatston score was used in all analyses.27
Statistical Analysis
All analyses were performed with the use of Stata, version 8.0 (Stata Corporation). Means, SDs, and proportions were used to summarize the characteristics of the study sample. Continuous variables were compared by ANOVA, and categorical variables were compared by the 2 statistic. When gender and ethnic groups were compared, ANOVA was used to assess racial differences of continuous variables among the 8 gender-ethnic groups.
Multivariable Poisson regression was used to examine the association between risk group, gender, and ethnicity and dyslipidemia in the MESA population. Several different sets of models were constructed to examine each outcome of interest: dyslipidemia prevalence, treatment, and control. For each outcome, 3 models were examined so that changes in the parameter estimate with the addition of risk factors and socioeconomic factors could be examined. Model 1 adjusted for age and clinical site and included gender and ethnicity. Model 2 added risk factors (body mass index, hypertension, diabetes, current smoking, and family history of heart attack). Model 3 added socioeconomic (education, employment status, income, household size, residential status) and healthcare access (source of usual medical care and health insurance coverage) variables to model 2.
The presence and severity of CAC across groups defined by risk and treatment recommendations were examined by ordered logistic regression with outcome categories of CAC <0, CAC >0 and <400, and CAC 400. The assumption of homogeneity of odds ratios across thresholds of CAC was tested and met.
Results
A total of 6814 men and women (38% non-Hispanic white, 28% black, 12% Chinese, 22% Hispanic) between the ages of 45 and 84 years completed the first MESA examination. Non-Hispanic whites were recruited at all 6 sites, blacks were recruited at 5 of 6 sites (not St Paul), Chinese were recruited predominantly in Chicago and Los Angeles, and Hispanics were recruited primarily in northern Manhattan, St Paul, and Los Angeles. The majority of both non-Hispanic whites and blacks reported being born in the United States or Puerto Rico (>90%); 96% of Chinese and 58% of Hispanic subjects reported being born outside the United States. Among the Hispanics born outside the United States or Puerto Rico, birthplace was reported as Mexico in 43%, Dominican Republic in 20%, South America in 15%, Central America in 7%, and other countries in 15%. The characteristics of the 6704 MESA participants with complete data on lipid and lipoprotein concentrations are shown in Table 1.
Observed lipid and lipoprotein cholesterol concentrations are provided in Table 2; all measures differed significantly by gender-ethnic group (P<0.001). The overall observed total cholesterol concentration was 193.5 mg/dL. The lowest concentrations were observed in black men (181.4 mg/dL), and the highest concentrations were observed in non-Hispanic white women (201.3 mg/dL). LDL cholesterol concentrations ranged from 113.5 mg/dL in black men to 119.6 mg/dL in Hispanic women, with an overall average of 117.2 mg/dL.
Descriptive results with regard to 10-year risk of coronary heart disease, dyslipidemia prevalence, treatment, and control are shown in Table 3; all measures differed significantly by gender-ethnic group (P<0.001). The 10-year risk of coronary heart disease differed primarily by gender and ranged from 3.8% in non-Hispanic white women to 13.4% in black men. The prevalence of dyslipidemia was 29.3% overall and ranged from 21.0% in Chinese women to 36.9% in non-Hispanic white men. Lipid-lowering drug therapy was reported by 15.8% of MESA participants, ranging from 12.5% in Chinese men to 19.2% in non-Hispanic white men; 54.0% of persons with dyslipidemia reported lipid-lowering drug treatment, ranging from 39.4% in Hispanic men to 74.1% of Chinese women.
In the total MESA population, LDL cholesterol concentrations were below the ATP III–defined drug treatment initiation threshold for 85.0%, ranging from 78.5% of Hispanic men to 93.3% of Chinese women, and LDL cholesterol concentrations were below the ATP III–defined drug treatment goal for 67.4%, ranging from 58.6% of Hispanic men to 79.5% of Chinese women. Of persons with dyslipidemia, only 40.6% were controlled to goal, ranging from 27.0% of Hispanic men to 61.2% of Chinese women; 75.3% of persons with treated dyslipidemia were controlled to goal, ranging from 65.7% of black women to 86.2% of non-Hispanic white women.
Age-specific results with regard to dyslipidemia prevalence, treatment, and control are provided in Table 4. The general pattern is consistent with a greater prevalence of dyslipidemia in the older age groups, a finding that is significant (P<0.001) after adjustment for gender, ethnicity, clinic site, risk factors, and socioeconomic and healthcare access variables. This general pattern was observed across gender and ethnic groups. Prevalence of treatment was greater in the older age groups, at least until age 75 years; however, this finding was not significant after adjustment for risk factors and socioeconomic and healthcare access variables. No difference was observed across age groups in control among persons with treated dyslipidemia.
Prevalence ratios (and corresponding 95% CIs) comparing gender and ethnic groups with respect to dyslipidemia prevalence, treatment, and control are shown in Table 5. In regard to gender comparisons, men were &30% more likely than women to have dyslipidemia; adjustment for risk factors and socioeconomic and healthcare access variables had no substantive effect on these findings. Men were &20% less likely than women to report drug treatment among the subset with dyslipidemia. Adjustment for risk factors and socioeconomic and healthcare access variables had no substantive effect on findings related to treatment of dyslipidemia. Among persons with dyslipidemia, men were &30% less likely than women to have their dyslipidemia controlled; in the treated subgroup, men were &10% less likely to be controlled. Among all MESA participants, men were &15% less likely than women to have their dyslipidemia controlled. Adjustment for risk factors and socioeconomic and healthcare access variables had no substantive effect on findings related to control of dyslipidemia.
With regard to ethnic comparisons, Chinese participants were 20% less likely than non-Hispanic whites to have dyslipidemia, and this difference was somewhat attenuated by adjustment for risk factors and socioeconomic and healthcare access variables. No difference was observed between blacks, Hispanics, and non-Hispanic whites. Hispanics were &20% and blacks were &15% less likely than non-Hispanic whites to report drug treatment. This difference was substantially attenuated by adjustment for socioeconomic and healthcare access variables for Hispanics. No significant differences were observed in drug treatment between Chinese and non-Hispanic white participants with dyslipidemia. Among participants with dyslipidemia (whether treated or not), blacks and Hispanics were &30% less likely than non-Hispanic whites to have their dyslipidemia controlled; in the treated subgroup, blacks and Hispanics were 16% and 6% (P=NS) less likely to be controlled. Adjustment for socioeconomic and healthcare access variables attenuated these findings substantially. Among all MESA participants, ethnic differences in prevalence of dyslipidemia control were <10%; however, these relatively small disparities were significant when blacks were compared with non-Hispanic whites. Adjustment for risk factors and socioeconomic and healthcare access variables attenuated these relationships substantially.
When classified into ATP II risk categories, 34.8% (2330/6704) of MESA participants were low risk, 43.6% (2925/6704) were intermediate risk, and 21.6% (1449/6704) were high risk (coronary heart disease risk equivalent). The prevalence of dyslipidemia was 11.7%, 33.6%, and 48.9% across these categories (P<0.001). Dyslipidemia treatment and control status is shown by ATP III risk category in Figure 1. Few low-risk participants qualified for dyslipidemia solely on the basis of high untreated LDL cholesterol concentrations. More than 80% of the low-risk group was treated, whereas only half of the intermediate- and high-risk groups were treated (P<0.001). Almost all treated low-risk participants were controlled versus &80% of treated intermediate-risk participants and half of treated high-risk participants (P<0.001). Dyslipidemia control is shown by gender, ethnicity, and ATP III risk category in Figure 2. The difference in control across ATP III risk categories is present across gender and ethnic groups.
The distribution of CAC score by ATP III risk-based treatment category is shown in Table 6. The presence and severity of CAC were greater in persons who met criteria for intermediate and high risk and in persons who met criteria for lipid-lowering drug treatment; however, the high-risk group that did not meet criteria for drug treatment had greater prevalence and severity of CAC than either of the lower-risk groups that did meet criteria for lipid-lowering drug treatment. These results were confirmed after adjustment for age, gender, ethnicity, and clinic site. Persons who met ATP III criteria for lipid-lowering drug treatment had an odds ratio for greater prevalence and severity of CAC of 1.59 (95% CI, 1.42 to 1.78; P<0.001). In comparison with low-risk individuals, intermediate- and high-risk participants had odds ratios of 1.67 (95% CI, 1.47 to 1.88; P<0.001) and 2.12 (95% CI, 1.82 to 2.47; P<0.001), respectively. The interaction of risk and treatment categories was examined and was not significant (P=0.31). Overall, 46.0% of lipid-lowering drug treatment–eligible participants were not receiving treatment. The proportion not treated differed by presence and severity of CAC, with 48.0%, 46.8%, and 39.6% of eligible persons with no CAC, with CAC >0 and <400, and with CAC 400 not receiving treatment, respectively (P for difference=0.04).
Discussion
In this middle-aged and older multiethnic cohort of people free of clinical cardiovascular disease, the prevalence of drug treatment–eligible dyslipidemia, as defined in ATP III, was &29%. Overall, 16% of the population reported treatment with lipid-lowering drugs, including 54% of those with dyslipidemia. Dyslipidemia was more common in men than in women and was treated and controlled less often in men than in women. Dyslipidemia prevalence differed little across ethnic groups, with the exception of a lower prevalence in Chinese subjects. Drug treatment also differed little across ethnic groups, with the exception of a lower prevalence of treatment reported by Hispanic subjects. Among persons with dyslipidemia, control of dyslipidemia was achieved less commonly in blacks and Hispanics than in non-Hispanic whites. Control of dyslipidemia was achieved less commonly in high-risk and intermediate-risk than in low-risk individuals. These results support several conclusions. Dyslipidemia, as defined by ATP III, is common in a population free of known clinical cardiovascular disease. Dyslipidemia treatment and control is far from optimal. The highest risk group has the lowest level of control, and there is evidence of gender and ethnic disparities in both treatment and control.
The findings related to gender disparities may reflect, at least in part, the combined effects of gender differences in risk-based thresholds for the definition of dyslipidemia, healthcare-seeking behaviors, and access to healthcare. Because male gender is recognized to increase the risk of coronary heart disease by the Framingham risk score, even if total and LDL cholesterol concentrations are equal in men and women, men will have cholesterol concentrations that more often cross the treatment threshold. Furthermore, men will more often meet criteria for a lower treatment goal. Women are more likely than men to have both health insurance and an ongoing source for primary care28 and are reported to seek healthcare services more often than men.29 These behavioral differences could explain part of the observed gender differences in treatment and control. Adjustment for healthcare access did not attenuate our findings; however, our measures of access did not include a measure of healthcare-seeking behavior.
Ethnic differences in prevalence of dyslipidemia were observed only for Chinese subjects, who had the lowest prevalence of dyslipidemia. This difference could be related to dietary and other cultural differences that result in lower total and LDL cholesterol concentrations.30 Chinese subjects were also less likely to report a family history of heart attack or, at least among women, current cigarette smoking. These risk factor differences could lead to the classification of a greater proportion of Chinese (than non-Hispanic whites) into a lower-risk group, with correspondingly higher treatment initiation and goal thresholds.
The observed ethnic disparities in treatment and control, with the relative deficits observed in blacks and Hispanics, are potentially due to ethnic differences in healthcare-seeking behaviors and access to care. Black and Hispanic Americans are well known to have lower insurance coverage rates and poorer access to care, as exemplified by greater reliance on emergency departments for healthcare services.29 This contention is supported by the results of analyses performed to examine whether the observed differences in dyslipidemia prevalence, treatment, and control could be attributed to differences in risk factors for coronary heart disease, socioeconomic characteristics, and healthcare access variables. Ethnic differences in treatment were attenuated more by adjustment for socioeconomic characteristics and healthcare access variables than by adjustment for other risk factors. Ethnic differences in control were attenuated by adjustment for both risk factors and socioeconomic and healthcare access variables. These patterns were especially apparent among Hispanics. These observations support the speculation that the ethnic disparity in treatment relates to differences in access to care, and the ethnic differences in control relate to differences in both access to care and the risk-specific treatment thresholds. The relative absence of ethnic disparities in control among persons with treated dyslipidemia supports the conclusion that the medications, when used, may be equally effective across ethnic groups. In contrast, neither sets of variables accounted for an appreciable proportion of the observed gender differences, suggesting that other factors underlie the observed gender differences.
The results of analyses of presence and severity of CAC by ATP III risk-based treatment group support the conclusion that the risk estimation process incorporated into ATP III distinguishes between groups that differ with respect to CAC. However, the discrimination was far from perfect. In addition, the magnitude of undertreatment observed in MESA differed minimally by presence and severity of CAC. This observation is not surprising because CAC was measured after the lipid-lowering treatment status had been determined; hence, the participants’ healthcare providers had no knowledge of the CAC scores when making treatment recommendations. These findings support the speculation that the providers were not very effective at targeting treatment to the highest-risk patients, at least insofar as presence and severity of CAC correlate with risk. Although CAC has been shown to predict risk of cardiovascular events,31 CAC-guided treatment has not been demonstrated to reduce progression of CAC32,33 or event rates, although little relevant research has been conducted to date. To the extent that the presence and severity of CAC might improve the ability to predict who might benefit from lipid-lowering drug treatment, the discriminatory ability of the ATP III risk-based algorithm might be enhanced considerably by information about CAC. Additional research is needed to investigate this possibility, including trials in persons with CAC who do not otherwise meet current criteria for lipid-lowering therapy. The urgency of this research is underscored by the observation that many drug-eligible persons with substantial CAC were not treated and many persons who did not qualify for drug treatment had substantial CAC.
This study is limited by the exclusion of persons with clinical cardiovascular disease, and therefore we cannot address secondary prevention. In addition, the study population was limited to 4 ethnic groups and 6 geographic areas in the United States; hence, these results may not be representative of other ethnic groups or of nationally representative patterns. The recruitment process was designed to produce a study population that was representative of residents without clinical cardiovascular disease; however, it is possible that participants were more health conscious than nonparticipants. The likely effect of this potential bias could be to lead to an underestimation of dyslipidemia prevalence and overestimation of treatment and control rates. Gender, ethnicity, and risk group comparisons could be biased if the magnitude of this potential selection bias differed by 1 or more of these characteristics. Finally, data collection spanned a period that included time before the release of ATP III; hence, these results should be interpreted as describing the scope of the challenge facing implementation of the ATP III guidelines rather than as evidence about the relative success or failure of implementation efforts. The challenge is greatest for the highest-risk group, among which three quarters were not controlled, but was substantial among the intermediate-risk group, among which three fifths were not controlled. This pattern of lesser control at higher risk is due, to a substantial extent, to the lower LDL cholesterol goal applied to the higher-risk groups. Quilliam et al34 provided insight into this challenge in an analysis of data from a managed care population. Among patients treated with HMG-CoA reductase inhibitors in early 2001, control to LDL cholesterol goals was 59.8% when ATP II guidelines were used and 53.0% when ATP III guidelines were used.34 We observed control rates that differed markedly by risk group among treated participants, from almost all treated low-risk persons to approximately half of the treated high-risk persons. This pattern is consistent with results from the Lipid Treatment Assessment Project (L-TAP) study that showed control rates of 68%, 37%, and 18% among low-risk, high-risk, and coronary heart disease patients, respectively, based on ATP II criteria, although our results showed higher control rates across risk groups than were observed in the L-TAP population in 1996–1997.7 Although additional research will be required to evaluate progress toward the goal of implementation, it is clear that the public health challenge posed by cholesterol control is substantial. According to the ATP III report, &16 million US adults without coronary heart disease qualify for lipid-lowering drug treatment.3 If our results are applied to this estimate, 7.4 million adults in the United States need lipid-lowering therapy initiated, and another 2.3 million adults need intensification of therapy to meet ATP III goals.
These results support several conclusions. Dyslipidemia requiring drug treatment is common in the middle-aged and older adult population of the United States among persons with no evidence of clinical cardiovascular disease. Rates of treatment and control of dyslipidemia are far from optimal, especially among the intermediate- and high-risk groups, and provide evidence of gender- and ethnicity-related disparities. The utility of incorporating CAC screening into the risk stratification and treatment process should be investigated in light of the substantial proportions of persons with CAC who are currently classified as not requiring treatment. Undertreatment of persons with dyslipidemia is a major public health challenge. Given the significance of cardiovascular disease as a public health problem in the United States and the proven benefits of lipid-lowering therapy for primary prevention, efforts to improve the treatment and control of dyslipidemia and to eliminate disparities in dyslipidemia management should be considered among our highest national healthcare quality improvement priorities.
Acknowledgments
This research was supported by contracts N01-HC-95159 through N01-HC-95165 and N01-HC-95166 from the National Heart, Lung, and Blood Institute. Staff scientists from the National Heart, Lung, and Blood Institute were involved in the design and conduct of the study, the oversight of the data collection, management, and analysis processes, and the review and approval of this article. The authors thank the other investigators, the staff, and the participants of the MESA Study for their valuable contributions. A full list of participating MESA investigators and institutions can be found at http://www.mesa-nhlbi.org.
Disclosures
Dr Goff reports having received speaker’s honoraria from Pfizer (<$10 000) and having served on the Preventive Cardiology Advisory Board of Pfizer (<$10 000). Dr Blumenthal reports having served on the speaker’s bureaus of Pfizer, Merck, KOS, Astra-Zeneca, and Schering-Plough (all <$10 000) and having received speaker’s honoraria from Pfizer, Merck, KOS, Astra-Zeneca, and Schering-Plough (all <$10 000). The remaining authors report no conflicts of interest.
References
American Heart Association. Heart Disease and Stroke Statistics—2004 Update. Dallas, Tex: American Heart Association; 2003.
Grundy SM, Cleeman JI, Merz CN, Brewer HB Jr, Clark LT, Hunninghake DB, Pasternak RC, Smith SC Jr, Stone NJ. Implications of recent clinical trials for the National Cholesterol Education Program Adult Treatment Panel III guidelines. J Am Coll Cardiol. 2004; 44: 720–732.
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): final report. Circulation. 2002; 106: 3143–3421.
Goff DC Jr, Gu L, Cantley LK, Parker DG, Cohen SJ. Enhancing the quality of care for patients with coronary heart disease: the design and baseline results of the Hastening the Effective Application of Research Through Technology (HEART) trial. Am J Manag Care. 2002; 8: 1069–1078.
Goff DC Jr, Gu L, Cantley LK, Sheedy DJ, Cohen SJ. Quality of care for secondary prevention for patients with coronary heart disease: results of the Hastening the Effective Application of Research Through Technology (HEART) trial. Am Heart J. 2003; 146: 1045–1051.
Banks T, Ali N. Coronary care physician 1994–2000 adherence to 1993 National Cholesterol Education Program diet and lipid recommendations. J Natl Med Assoc. 2001; 93: 87–91.
Pearson TA, Laurora I, Chu H, Kafonek S. The Lipid Treatment Assessment Project (L-TAP): a multicenter survey to evaluate the percentages of dyslipidemic patients receiving lipid-lowering therapy and achieving low-density lipoprotein cholesterol goals. Arch Intern Med. 2000; 160: 459–467.
Stafford RS, Blumenthal D, Pasternak RC. Variations in cholesterol management practices of U.S. physicians. J Am Coll Cardiol. 1997; 29: 139–146.
Sueta CA, Chowdhury M, Boccuzzi SJ, Smith SC Jr, Alexander CM, Londhe A, Lulla A, Simpson RJ Jr. Analysis of the degree of undertreatment of hyperlipidemia and congestive heart failure secondary to coronary artery disease. Am J Cardiol. 1999; 83: 1303–1307.
Smith SC Jr. Clinical treatment of dyslipidemia: practice patterns and missed opportunities. Am J Cardiol. 2000; 86: 62L–65L.
McBride P, Schrott HG, Plane MB, Underbakke G, Brown RL. Primary care practice adherence to National Cholesterol Education Program guidelines for patients with coronary heart disease. Arch Intern Med. 1998; 158: 1238–1244.
Bramlet DA, King H, Young L, Witt JR, Stoukides CA, Kaul AF. Management of hypercholesterolemia: practice patterns for primary care providers and cardiologists. Am J Cardiol. 1997; 80: 39H–44H.
Nieto FJ, Alonso J, Chambless LE, Zhong M, Ceraso M, Romm FJ, Cooper L, Folsom AR, Szklo M. Population awareness and control of hypertension and hypercholesterolemia: the Atherosclerosis Risk in Communities Study. Arch Intern Med. 1995; 155: 677–684.
The Clinical Quality Improvement Network (CQIN) Investigators. Low incidence of assessment and modification of risk factors in acute care patients at high risk for cardiovascular events, particularly among females and the elderly. Am J Cardiol. 1995; 76: 570–573.
Giles WH, Anda RF, Jones DH, Serdula MK, Merritt RK, DeStefano F. Recent trends in the identification and treatment of high blood cholesterol by physicians: progress and missed opportunities. JAMA. 1993; 269: 1133–1138.
Cohen MV, Byrne MJ, Levine B, Gutowski T, Adelson R. Low rate of treatment of hypercholesterolemia by cardiologists in patients with suspected and proven coronary artery disease. Circulation. 1991; 83: 1294–1304.
Hoerger TJ, Bala MV, Bray JW, Wilcosky TC, LaRosa J. Treatment patterns and distribution of low-density lipoprotein cholesterol levels in treatment-eligible United States adults. Am J Cardiol. 1998; 82: 61–65.
Straka RJ, Taheri R, Cooper SL, Tan AW, Smith AC. Assessment of hypercholesterolemia control in a managed care organization. Pharmacotherapy. 2001; 21: 818–827.
Abookire SA, Karson AS, Fiskio J, Bates DW. Use and monitoring of "statin" lipid-lowering drugs compared with guidelines. Arch Intern Med. 2001; 161: 53–58.
Massing MW, Foley KA, Carter-Edwards L, Sueta CA, Alexander CM, Simpson RJ Jr. Disparities in lipid management for African Americans and Caucasians with coronary artery disease: a national cross-sectional study. BMC Cardiovasc Disord. 2004; 4: 15.
Bild DE, Bluemke DA, Burke GL, Detrano R, Diez Roux AV, Folsom AR, Greenland P, Jacob DR Jr, Kronmal R, Liu K, Nelson JC, O’Leary D, Saad MF, Shea S, Szklo M, Tracy RP. Multi-ethnic study of atherosclerosis: objectives and design. Am J Epidemiol. 2002; 156: 871–881.
Chang JJ, Rabinowitz D, Shea S. Sources of variability in blood pressure measurement using the Dinamap PRO 100 automated oscillometric device. Am J Epidemiol. 2003; 158: 1218–1226.
Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem. 1972; 18: 499–502.
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.
Breen JF, Sheedy PF, Schwartz RS, Stanson AW, Kaufmann RB, Moll PP, Rumberger JA. Coronary artery calcification detected with ultrafast CT as an indication of coronary artery disease. Radiology. 1992; 185: 435–439.
Carr JJ, Crouse JR III, Goff DC Jr, D’Agostino RB Jr, Peterson NP, Burke GL. Evaluation of subsecond gated helical CT for quantification of coronary artery calcium and comparison with electron beam CT. AJR Am J Roentgenol. 2000; 174: 915–921.
Agatston AS, Janowitz WR, Hildner FJ, Zusmer NR, Viamonte M Jr, Detrano R. Quantification of coronary artery calcium using ultrafast computed tomography. J Am Coll Cardiol. 1990; 15: 827–832.
Maiese DR. Healthy people 2010: leading health indicators for women. Womens Health Issues. 2002; 12: 155–164.
Lethbridge-Cejku M, Schiller JS, Bernadel L. Summary health statistics for U.S. adults: National Health Interview Survey, 2002. National Center for Health Statistics. Vital Health Stat 10 (222); 2004.
Huang MH, Schocken M, Block G, Sowers M, Gold E, Sternfeld B, Seeman T, Greendale GA. Variation in nutrient intakes by ethnicity: results from the Study of Women’s Health Across the Nation (SWAN). Menopause. 2002; 9: 309–319.
Greenland P, LaBree L, Azen SP, Doherty TM, Detrano RC. Coronary artery calcium score combined with Framingham score for risk prediction in asymptomatic individuals. JAMA. 2004; 291: 210–215.
Wong ND, Kawakubo M, LaBree L, Azen SP, Xiang M, Detrano R. Relation of coronary calcium progression and control of lipids according to National Cholesterol Education Program guidelines. Am J Cardiol. 2004; 94: 431–436.
Raggi P, Davidson M, Callister TQ, Welty FK, Bachmann GA, Hecht H, Rumberger JA. Aggressive versus moderate lipid-lowering therapy in hypercholesterolemic postmenopausal women: Beyond Endorsed Lipid Lowering with EBT Scanning (BELLES). Circulation. 2005; 112: 563–571.
Quilliam BJ, Perez HE, Andros V, Jones P. Quantifying the effect of applying the NCEP ATP III criteria in a managed care population treated with statin therapy. J Manag Care Pharm. 2004; 10: 244–250.(David C. Goff, Jr, MD, PhD; Alain G. Ber)