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Original Investigation |

Favorable Cardiovascular Risk Profile in Middle Age and Health-Related Quality of Life in Older Age FREE

Martha L. Daviglus, MD, PhD; Kiang Liu, PhD; Amber Pirzada, MD; Lijing L. Yan, PhD, MPH; Daniel B. Garside, BS; Joseph Feinglass, PhD; Jack M. Guralnik, MD, PhD; Philip Greenland, MD; Jeremiah Stamler, MD
[+] Author Affiliations

From the Department of Preventive Medicine (Drs Daviglus, Liu, Pirzada, Yan, Feinglass, Greenland, and Stamler, and Mr Garside), the Department of Medicine, Division of Geriatrics (Drs Daviglus, Liu, and Greenland), and the Department of Medicine, Division of General Internal Medicine (Dr Feinglass), Northwestern University, Feinberg School of Medicine, Chicago, Ill; and the Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, Bethesda, Md (Dr Guralnik). The authors have no relevant financial interest in this article.


Arch Intern Med. 2003;163(20):2460-2468. doi:10.1001/archinte.163.20.2460.
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Background  Life expectancy is greater for people with favorable midlife cardiovascular risk profiles (ie, low risk). However, some speculate that increased longevity may lead to large numbers of ill, disabled, older persons with lower quality of life. Few data exist on this important issue. This study evaluates the relationship of midlife low-risk status to quality of life and illness in older age.

Methods  Cohort of middle-aged adults from the Chicago Heart Association Detection Project in Industry (2692 women and 3650 men; baseline ages, 36-64 years [average age, 73.2 years in 1996]) without baseline (1967-1973) major electrocardiographic abnormalities or history of diabetes or myocardial infarction. Quality of life (12-item Health Status Questionnaire [HSQ-12] on physical, mental, and social well-being) and self-reported diseases were assessed after 26 years of follow-up. Baseline risk strata included low risk (favorable blood pressure and serum cholesterol levels, no smoking, and no minor electrocardiographic abnormalities); 0 risk factors (ie, no high risk factors but ≥1 risk factors not at favorable levels); or any 1, any 2, or 3 or more of the following 4 risk factors: high blood pressure, high serum cholesterol level, smoking, and minor electrocardiographic abnormalities. The HSQ-12 scores and disease outcomes for low risk were compared with other strata.

Results  Adjusted scores for physical, mental, social functioning, and disease-free outcomes were highest for low-risk individuals and decreased significantly with number of risk factors (eg, 58% of low-risk women had excellent/very good health compared with 28% of women with ≥3 risk factors).

Conclusions  Favorable cardiovascular risk profile in middle age is associated with better quality of life and lower risk of diseases in older age. Moreover, the fewer the risk factors, the higher the quality of life.

Figures in this Article

EXTENSIVE EVIDENCE has been amassed showing that major coronary risk factors, particularly adverse serum cholesterol and blood pressure levels and smoking, are powerful long-term predictors of cardiovascular morbidity and mortality.15 This knowledge has contributed to the development of prevention and control programs to curb the epidemic impact of coronary heart disease (CHD). Related to these and other efforts, mortality from CHD, cardiovascular disease (CVD), and all causes has declined steadily in the United States and other Western societies during the last several decades with a consequent gain in life expectancy. At present, an individual reaching age 65 years can expect to live on average nearly 18 additional years, and life expectancy is likely to continue to rise.6,7 However, some speculate that increased longevity may lead to greater morbidity, with a greater number of years afflicted by chronic illnesses and disabilities,811 resulting in lower quality of life.

The fear that increasing longevity leads to an older population of frail and disabled persons may be unfounded. Evidence suggests that middle-aged persons with healthier lifestyles not only survive longer, but their disability is postponed and compressed into fewer years.12 Thus, benefits of favorable levels of all major cardiovascular risk factors and/or a healthful lifestyle (ie, low-risk status) at younger ages may encompass not only lower age-specific mortality,13,14 greater longevity,13 and substantially lower health care costs15 but also higher quality of life (ie, prolongation of independent and healthy living) with less illness in older age. Few studies have examined the association of baseline risk factors with health-related quality of life, particularly in low-risk men and women.

We report on relations of baseline cardiovascular risk assessed in middle-aged men and women to subsequent health-related quality of life and morbidity in older age after an average follow-up of 26 years using data from the Chicago Heart Association Detection Project in Industry (CHA).

PARTICIPANTS AND BASELINE EXAMINATION

From November 1967 to January 1973, the CHA study screened 39 522 men and women 18 years and older and of varied ethnicities and socioeconomic levels, who were employed by 84 Chicago-area organizations. Standardized examination methods were used, as reported elsewhere.4,16 Briefly, screening was done by 2 trained and standardized field teams who measured height, weight, serum total cholesterol,17 and supine blood pressure. Participants completed a questionnaire about their demographic characteristics, smoking history, medical history, and medical treatment of hypercholesterolemia, hypertension, diabetes, and myocardial infarction (MI). Resting electrocardiograms (ECGs) were classified as showing major, minor, or no abnormalities based on criteria of the Hypertension Detection and Follow-up Program.18

FOLLOW-UP QUESTIONNAIRE

In 1996, a follow-up health survey was mailed to all surviving CHA study participants who were between 36 and 64 years old at baseline and were 65 years and older in 1996, hence eligible for this study (n = 13 262). For 92.6% of these individuals, current addresses were obtained from the Centers for Medicare & Medicaid Services (CMS, formerly Health Care Financing Administration) by matching study records with name, sex, date of birth, and Social Security number. When current addresses were not available from the CMS, effort was made to locate them through online searches and submission to Equifax Inc, McLean, Va. For questionnaires returned with forwarding addresses, a second mailing was sent. Of the 13 262 questionnaires mailed, 782 (5.9%) were returned by the postal service without forwarding addresses, and another 150 participants were reported by their next of kin to be recently deceased. Only 521 recipients (3.9%) explicitly refused to participate in the study. Questionnaires (n = 7381) were received from 59.9% of participants with available addresses (n = 12 330, including the explicit refusals), with an average follow-up of 25.8 years (Figure 1). The 4-page questionnaire included assessments of health-related quality of life, risk factors, habitual exercise pattern, alcohol consumption, smoking history, history of diseases and conditions (eg, MI, angina, congestive heart failure, stroke, and diabetes), and current medication use for hypertension, hypercholesterolemia, diabetes, and hormone therapy (for women). Institutional review board approval was granted to contact participants by mail 26 years after baseline examination.

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Figure 1.

Sample flowchart.

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EXCLUSIONS

Of the 7381 participants 65 years and older in 1996 who completed the questionnaire, 1039 were excluded for the following reasons: prevalent diseases at baseline (ie, history of physician-diagnosed or ECG evidence of MI [n = 60], major ECG abnormalities [n = 519], and physician-diagnosed diabetes [n = 142]), because quality of life at follow-up would be influenced by long-standing morbidity; missing baseline data on diabetes (n = 21), smoking (n = 2), blood pressure (n = 5), serum cholesterol level (n = 25), education (n = 6), height or weight (n = 2); or missing follow-up questionnaire data (n = 257). Thus, the present study is based on 2692 women and 3650 men 65 years and older (average age, 73.2 years), with complete data on baseline risk factors and follow-up measures of quality of life (Figure 1).

CARDIOVASCULAR RISK GROUPS

Participants free of MI, diabetes, and major ECG abnormalities were classified into 5 groups according to baseline CVD risk status. Those with favorable levels of all the following baseline characteristics were considered to be at low risk for CVD: systolic blood pressure (SBP)/diastolic blood pressure (DBP) 120/80 mm Hg or below and not receiving antihypertensive medication; serum cholesterol level below 200 mg/dL (<5.2 mmol/L); no current smoking; and no minor ECG abnormalities. Participants not at low risk were classified as having 0 risk factors (no high risk factors but 1 or more risk factors not at favorable levels), or any 1, any 2, or 3 or more of the following 4 risk factors: SBP 140 mm Hg or greater or DBP 90 mm Hg or greater or receiving antihypertensive medication19; serum cholesterol level 240 mg/dL or greater (≥6.2 mmol/L);20 current cigarette smoking; or any minor ECG abnormality.

QUALITY OF LIFE ASSESSMENT

The self-reported 12-item Health Status Questionnaire (HSQ-12), developed by Health Outcomes Research,21,22 was used to measure quality of life. Validity and reliability of the HSQ-12 in measuring quality of life in older individuals have been demonstrated.23,24 Similar to the Medical Outcomes Trust Short-Form Health Survey (SF-12),25 HSQ-12 provides measures of physical and social functioning and mental health by evaluating 8 health domains: (1) health perception, (2) physical functioning (ie, ability to perform daily tasks and activities), (3) role limitations attributable to physical health, (4) bodily pain, (5) energy/fatigue, (6) social functioning (ie, degree to which physical or emotional problems interfere with individual social activities), (7) role limitations attributable to mental health, and (8) mental health (ie, subjective evaluation of one's own emotional well-being). For each item, categorical responses ranging from 3 to 6 categories are scaled into numeric scores ranging from 0 (poorest health) to 100 (optimal health) according to HSQ-12 scoring protocol.22 Categorical responses to each HSQ-12 item were also dichotomized to indicate favorable outcomes (eg, excellent or very good self-rated health vs all others).

STATISTICAL ANALYSES

Analyses across the 5 risk groups were done separately for women and men. F tests (for continuous variables) or χ2 (for categorical variables) were used to detect statistically significant differences in baseline characteristics across the strata. General linear models were used to compute group mean domain scores adjusted for age (in 1996), race (African American or not), and baseline education (years). The risk group was entered in the linear models as a class variable. Linear trends were tested across these groups as ordinal variables with values of 1 to 5. Additional models were also adjusted for baseline body mass index (BMI). Sex-specific and age-, race-, and education-adjusted prevalence (percentage) of favorable HSQ-12 outcomes and self-reported CHD, CVD, other major chronic diseases, and current medication use for hypertension, hypercholesterolemia, and diabetes, were calculated by baseline risk status using general linear models. These values are covariate-adjusted least squares estimates. Linear trends were tested using logistic regression, with risk status as an ordinal variable. Since minor ECG abnormalities may represent only incidental findings, particularly in women,26 to examine impact of the 3 readily measured major preventable and modifiable risk factors (ie, blood pressure, serum cholesterol level, and smoking) on quality of life, all analyses were repeated on a subsample of 5973 individuals with no minor ECG abnormalities. Analyses were conducted using SAS statistical software (v8.02; SAS Institute Inc, Cary, NC).

BASELINE CHARACTERISTICS

There were 264 (9.8%) women and 229 (6.3%) men who met the criteria for low risk (Table 1). On average, at baseline low-risk men and women were younger, better educated, and had lower BMI. By definition, average serum cholesterol and blood pressure values were also markedly lower for low-risk subgroups compared with others. For example, for women at low risk, mean cholesterol level was lower by 35 mg/dL (0.9 mmol/L), and SBP and DBP were lower by 19 and 9 mm Hg, respectively, compared with women with any 1 risk factor. Response rate for low-risk persons to the 1996 health survey was 70.1% compared with 66.6%, 60.2%, 55.7%, and 51.0% of persons with 0, any 1, any 2, or 3 or more risk factors at baseline, respectively. Also, responders were apparently healthier at follow-up than nonresponders as reflected by higher 4-year postsurvey (1997-2000) age-adjusted mortality rates among nonresponders (ie, men, 22.3% [nonresponders] vs 15.1% responders; women, 18.2% nonresponders vs 12.7% responders [P<.001 for both]).

Table Graphic Jump LocationTable 1. Baseline Characteristics of 2692 Women and 3650 Men 65 Years or Older in 1996 by Baseline Risk Status, Chicago Heart Association Detection Project in Industry Study, 1967-1973
ADJUSTED PREVALENCE OF FAVORABLE HSQ-12 OUTCOMES

For each of the 12 items, age-, race-, and education-adjusted prevalence of favorable outcomes for physical, mental, and social functioning were highest for low-risk women and decreased with number of cardiovascular risk factors (P values for trend ranged from <.05 to <.001) (Table 2). For example, the percentage of low-risk women perceiving themselves as having excellent or very good health was more than double that of women with 3 or more risk factors (57.6% vs 27.9%). In general, similar results were observed among men, except for items dealing with mental health (eg, feeling downhearted and blue and being a happy person), for which no significant differences in prevalence across groups were observed.

Table Graphic Jump LocationTable 2. Multivariable-Adjusted Prevalence of Favorable Responses to 12 Items in the HSQ-12 Among 2692 Women and 3650 Men 65 Years or Older in 1996 by Baseline Risk Status, 1967-1973*

With the exclusion of persons with minor ECG abnormalities, results were consistent with those for the full sample and remained statistically significant. Figure 2 shows examples of favorable outcomes for 4 HSQ-12 items representing physical, mental, and social aspects of quality of life. For both women and men, percentages of low-risk individuals reporting excellent or very good health and no limitations in walking several blocks were markedly higher than for those with 0, any 1, any 2, or all 3 risk factors (all P values for trend <.001). Modest differences in social functioning across the risk groups were observed for both men and women (P<.05); differences in mental health (feeling downhearted and blue) across risk groups were seen in women (P = .02) but not in men (P = .48).

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Figure 2.

Multivariable-adjusted prevalence of favorable outcomes for 4 items in the 12-item Health Status Questionnaire (HSQ-12) at 26-year follow-up by baseline risk status (see asterisk footnote in Table 1 for definition of risk status) for 2564 women and 3409 men 65 years or older in 1996. Adjusted for age in 1996, race (indicator for African American), and baseline education (in years). The 4 items in the HSQ-12 are health perception: excellent or very good self-rated health; no limitation in walking several blocks (1 of the 3 physical functioning items); no or slight interference from physical or mental health in social functioning; feeling downhearted or blue none or a little of the time (1 of the 3 mental health items). Persons with a history of diagnosed diabetes, myocardial infarction, or any (minor or major) electrocardiographic abnormalities at baseline were excluded. P values for linear trend across 5 risk strata based on logistic regressions using "risk status" as an ordinal variable with values ranging from 1 to 5: for women, P<.001 for all except mental health (P = .02); for men, P<.001 for health perception and walking, P =.03 for social functioning, and P = .48 for mental health. RF indicates risk factor.

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ADJUSTED MEAN HSQ-12 DOMAIN SCORES

Age-, race-, and education-adjusted mean HSQ-12 scores for the 8 domains by risk factor group and sex are given in Table 3. There is an inverse graded relationship between baseline risk status and all 8 health-domain scores for women, and for health perception, physical functioning, and role limitations attributable to physical health for men. The better the risk profile, the higher the score (eg, low-risk women had an adjusted health perception score of 70.2, which is, respectively, 7.2, 9.6, 13.0, and 24.9 points higher than for women with 0, any 1, any 2, and ≥3 risk factors). In general, the inverse associations were stronger for physical health (ie, physical functioning, physical role limitations, and bodily pain) than for mental or social well-being. Tests for linear trend showed that most were statistically significant at P<.001. Similar differences in scores across groups were observed with exclusion of persons with minor ECG abnormalities at baseline. Additional adjustment for BMI, a risk factor correlated with other CVD risk factors such as blood pressure and cholesterol, lowered the HSQ-12 mean scores only slightly. For example, health perception scores for women ranged from 69.0 (low risk) to 46.0 (≥3 risk factors) and for men from 70.4 to 59.3.

Table Graphic Jump LocationTable 3. Multivariable-Adjusted Mean Scores for 8 HSQ-12 Domains and Mean Summary Scores at 26-Year Follow-up According to Baseline Risk Status*
DISEASES AND MEDICATION USE

Age-, race-, and education-adjusted prevalence of diseases was strong and graded across risk groups (Figure 3). Low-risk men and women reported the lowest prevalence of CHD, CVD, and other chronic diseases compared with men and women with unfavorable baseline risk factor findings. For example, there was almost a 3-fold difference in self-reported prevalence of CHD and CVD between low-risk women and those with 3 or more risk factors (6.7% vs 21.4% and 11.9% vs 31.0%, respectively [P values for trend <.001]). Similarly, significant and graded differences existed for medication use for hypertension, hypercholesterolemia, and/or diabetes across risk strata (eg, 26.1% of low-risk women vs 76.7% of women with ≥3 risk factors reported medication use; corresponding figures for men were 25.3% vs 67.0% [P values for trend <.001]).

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Figure 3.

Multivariable-adjusted prevalence of self-reported coronary heart disease (CHD), cardiovascular disease (CVD), and any of 22 major diseases at 26-year follow-up by baseline risk status (see asterisk footnote in Table 1 for definition of risk status) for 2692 women and 3650 men 65 years or older. Adjusted for age in 1996, race (indicator for African American), and baseline education (in years). CHD includes myocardial infarction and angina; CVD, CHD, congestive heart failure, stroke, arteriosclerosis, and other heart diseases; and any disease, 6 groups of diseases in CVD, lung cancer, stomach cancer, intestinal cancer, rectal cancer, female cancers (breast cancer, ovarian cancer, and uterine cancer), prostate cancer, leukemia, other cancers excluding skin cancer, diabetes, pneumonia, emphysema, liver disease, kidney disease, Alzheimer disease, hip fracture, and other major diseases. P<.001 for linear trend across 5 risk strata for all outcomes for both men and women based on logistic regressions using "risk status" as an ordinal variable with values ranging from 1 to 5. RF indicates risk factor.

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Our findings, based on an average follow-up of 26 years, show that favorable levels of all major CVD risk factors in middle age were associated with substantially better health-related quality of life and less illness in older age. Higher proportions of men and women with low cardiovascular risk status in middle age had no limitations in basic activities associated with physical, mental, and social functioning; contrariwise, prevalence of having no limitations decreased with number of cardiovascular risk factors. Associations tended to be stronger, more graded, and more significant for women than for men and for physical and social functioning than for mental health, possibly because of lower response rates among persons with poorer mental and social functioning. Furthermore, age-, race-, and education-adjusted prevalence of cardiovascular and noncardiovascular diseases and history of medication use for certain conditions (ie, hypertension, hypercholesterolemia, and/or diabetes) were lowest among low-risk men and women. In addition, there were corresponding findings with consideration of only the 3 major coronary risk factors: serum cholesterol, blood pressure, and cigarette smoking. These traits are important because of their high prevalence and impact on risk, and their prevention could have a great influence on longevity,13 health care costs,15 and (as demonstrated here) quality of life and morbidity.

With the population segment 65 years and older expanding rapidly in the United States and other industrialized countries, an evident trend in health care is the shift toward caring for increasing numbers of older persons with chronic diseases and disabilities.27 Some fear that increased life expectancies will lead to rising numbers of frail, disabled, and institutionalized older persons,911 suggesting that one reason for recent increases in prevalence of chronic diseases and their accompanying limitations among older persons may be longer survival. However, it has also been proposed that age of onset of morbidity can be postponed, reducing years of disability and disease to a brief period before death.28 Hence, preserving quality of life at older ages has become an increasingly important issue.

To date, little information has emerged on the long-term impact of cardiovascular risk factors and related lifestyle habits measured in youth and middle age on quality of life in older age. The main focus of research has been on physical disability and specific components of functional health status, not on the entire spectrum of quality of life (ie, the subjective sense of well-being encompassing physical, mental, and social aspects of life).29 The available longitudinal studies have mostly assessed impact on disability of single risk factors rather than combinations of risk factors.3033 Prior studies also lack low-risk subcohorts of adequate size to use as a benchmark for comparison. The Framingham Disability Study (FDS) examined associations of multiple characteristics with functional status 21 years later among 748 men and 726 women (ages 35-68 years at baseline). For men, age, alcohol intake, cigarette smoking, and ventricular rate were significantly and inversely related to functional status; higher education was associated with better functional status. For women, the only significant predictors were age and education.30 Another report from the FDS on 2021 surviving participants (baseline ages, 28-62 years) showed a relationship of CHD risk factors with 27-year disability in the absence of diagnosed CVD at follow-up. Hypertension, smoking, and high BMI were associated with greater disability in women. Among men, the only statistically significant risk factor was hypertension.31 Results from a study of 3263 Hawaiian men of Japanese ancestry from the Honolulu Heart Study (baseline ages, 45-68 years) followed up for 28 years show that lower levels of blood pressure and serum glucose, nonsmoking, and absence of obesity were predictors of healthy aging (ie, freedom from clinical illness and from physical and cognitive impairment).32

The only other study on risk factor combinations and disability involves a cohort of former University of Pennsylvania students (1355 men and 386 women; average age, 43 years in 1962). Middle-aged individuals with better health behaviors (based on smoking, BMI, and exercise) had significantly less disability in older age (average age, 75 years) 32 years later compared with others.12 Moreover, when the course of disability prior to death was examined among 418 deceased individuals, those with fewer risk factors experienced less overall disability, and accelerated decline of functional ability was delayed before death.34 While earlier studies are limited by small sample sizes and homogeneous education, our study involves a large cohort of men and women of varied ethnicity and education. Data from large numbers of surviving individuals, with measured baseline risk factors and long follow-up, enable us to examine the association of the spectrum of cardiovascular risk profile with quality of life 26 years later. Assessing effects of cardiovascular risk profile, rather than individual risk factors, is also of public health importance because, although prevalence of most major risk factors has declined in the United States, the proportion of the population with 1 or more CVD risk factors (hence, at increased risk for CVD) remains dismally high. In a national telephone survey, 35% of respondents reported having 1 CVD risk factor; 29% reported 2; and 18% reported 3 or more risk factors.35

Resistance to major age-related diseases, first and foremost CVDs—major causes of morbidity, disability, and mortality in older age36—has been hypothesized to play an important role in healthy aging, favorable quality of life, and longevity.37,38 Data from the present study support this concept. Among CHA study survivors, adjusted self-reported prevalence of disease was lowest among low-risk men and women and increased with number of risk factors. For example, prevalence of CVD in low-risk men and women was less than half that of survivors with 3 or more risk factors. Thus, a larger proportion of low-risk individuals survived to older age free of cardiovascular and other chronic diseases. A reasonable further inference from the CHA data is that so far the low-risk group (average age, 72 years) experienced compression of morbidity.28 It remains to be seen whether this favorable situation persists beyond age 72 years. This question can be answered only by continued follow-up of this and other low-risk groups over enough years to accrue total life experience (ie, follow-up to mortality) for all or most of the people in these cohorts.

Only a small minority of the cohort (<10% of the entire 39 522 participants) met the criteria for low risk at the baseline examination in 1967-1973. Of note, participants with 0 risk factors (ie, nonsmokers with intermediate [but not favorable] levels of serum cholesterol and blood pressure and no minor ECG abnormalities [20.2% of all participants]) also had better outcomes than those with 1 or more high risk factors. Prevalence of low-risk status was similarly low in other cohorts. For example, only about 7% of the Nurses' Health Study cohort met criteria for low risk defined by lifestyle and dietary factors (nonsmoking, moderate/vigorous exercise ≥30 min/d, BMI [calculated as weight in kilograms divided by the square of height in meters] <25, and a diet score in the top 2 quintiles).14 Furthermore, only 18% of respondents to a national telephone survey (ages ≥18 years) reported having no major CVD risk factors (but not necessarily favorable levels).35 Nonetheless, the past few decades saw significant declines not only in CVD mortality and morbidity39,40 but also (in the past 2 decades) in chronic disability prevalence rates among older persons in the United States,4143 possibly due to decreasing prevalence of major CVD risk factors and increase in prevalence of low-risk individuals.

One limitation of our study is possible selection bias related to the response rate (approximately 60%) to the questionnaire. Difficulties of long-term follow-up are well documented, especially in studies in which participants have not been contacted for decades, and response rates have been similar to ours.44 In our cohort, there was a graded inverse relation between number of baseline risk factors and response rate, possibly because nonresponders were in poorer current health, hence less motivated or less able to participate. This is consistent with the observation of a higher 4-year postsurvey mortality rate among nonresponders compared with responders. Hence, the observed associations between low-risk status and quality of life are almost certainly underestimates (ie, would likely have been stronger had we obtained a better response rate from higher-risk participants). A further limitation is that risk factors were measured at only a single point in time, and changes in the profiles of low-risk persons probably occurred during the 26-year follow-up, which is also likely to bias the results toward the null. Also, although participants with history of MI or diagnosis of diabetes at baseline were excluded, information was not collected to exclude those with other severe chronic conditions at initial examination, which could potentially influence quality of life. Exclusion of persons with history of MI or diabetes at baseline made the associations between midlife risk factors and older age quality of life more conservative. Furthermore, the CHA cohort was derived from employed persons in Chicago; thus, they were healthier than the general population and less likely to have severe chronic diseases at baseline. Finally, the use of participant-reported data on morbidity and medications, the most practical method of assessing disease status in large prospective studies, is also a limitation. However, recent reports show that self-reported morbidity is superior to data collected by physicians for predicting functional disability.45 Self-reports of ischemic heart disease were found to be accurate more than 80% of the time.46

The findings of our study demonstrate the beneficial effect of low-risk status in middle age for future health-related quality of life, including physical and social functioning and mental health. Current treatments (including drug treatment and lifestyle modifications) to control high blood pressure and serum cholesterol level, while effective, do not typically reduce morbidity and mortality to levels observed in low-risk individuals.47,48 Our data imply that primary prevention of major cardiovascular risk factors earlier in life is the key strategy not only to mitigate the epidemic of CHD and CVD in older age but also to improve quality of life with better health status. Although the critical goal of prevention must be to maximize the number of people in the low-risk group, this study also shows a clear gradient for health status in older age with number of risk factors. This implies that there may be substantial benefit in preventing shift to higher risk factor levels. This highlights the importance of comprehensive preventive strategies of simultaneously targeting all major CVD risk factors for achievement of the national goal of increased years of healthy life for older adults.

Corresponding author and reprints: Martha L. Daviglus, MD, PhD, Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, 680 N Lake Shore Dr, Suite 1102, Chicago, IL 60611 (e-mail: daviglus@northwestern.edu).

Accepted for publication July 29, 2003.

This research was supported by grants from the American Heart Association, Dallas, Tex, and its Chicago and Illinois affiliates; Illinois Regional Medical Program; National Heart, Lung, and Blood Institute, Bethesda, Md (grants R01 HL21010 and R01 HL62684); the Chicago Health Research Foundation, Chicago, Ill; private donors; and by an Established Investigator Award from the American Heart Association (Dr Daviglus).

We thank the officers and employees of the Chicago companies and organizations whose invaluable cooperation and assistance made this study possible. We also thank those involved in the Chicago Heart Association Detection Project in Industry. An extensive list of colleagues who contributed to this important endeavor is given in Cardiology (1993;82:191-222). We are also indebted to Linda Schiffer, MS, MPH, for her valuable contributions in the acquisition and management of data.

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Prineas  RJCastle  CHCurb  JDHarrist  RLewin  AStamler  J Hypertension detection and follow-up program: baseline electrocardiographic characteristics of the hypertensive participants. Hypertension. 1983;5IV160- IV189
PubMed Link to Article
Chobanian  AVBakris  GLBlack  HR  et al. and the National High Blood Pressure Education Program Coordinating Committee, The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA. 2003;2892560- 2572
PubMed Link to Article
Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults, 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;2852486- 2497
PubMed Link to Article
Radosevitch  DPruitt  M Twelve-Item Health Status Questionnaire (HSQ-12) Version 2.0.  Bloomington, Minn Health Outcomes Institute1995;
Health Outcomes Institute, Twelve-Item Health Status Questionnaire (HSQ-12) Version 2.0 User Guide.  Bloomington, Minn Health Outcomes Institute1996;
Bowling  AWindsor  J Discriminative power of the Health Status Questionnaire 12 in relation to age, sex, and longstanding illness: findings from a survey of households in Great Britain. J Epidemiol Community Health. 1997;51564- 573
PubMed Link to Article
Pettit  TLivingston  GManela  MKitchen  GKatona  CBowling  A Validation and normative data of health status measures in older people: the Islington Study. Int J Geriatr Psychiatry. 2001;161061- 1070
PubMed Link to Article
Ware  JEKosinski  MKeller  SD A 12-item short-form health survey: construction of scales and preliminary tests of reliability and validity. Med Care. 1996;34220- 233
PubMed Link to Article
Liao  YLiu  KDyer  A  et al.  Major and minor electrocardiographic abnormalities and risk of death from coronary heart disease, cardiovascular diseases and all causes in men and women. J Am Coll Cardiol. 1988;121494- 1500
PubMed Link to Article
Lubitz  JBeebe  JBaker  C Longevity and Medicare expenditures. N Engl J Med. 1995;332999- 1003
PubMed Link to Article
Fries  JF Aging, natural death, and the compression of morbidity. N Engl J Med. 1980;303130- 135
PubMed Link to Article
Tibblin  GSvardsudd  KWelin  LErikson  HLarsson  B Quality of life as an outcome variable and a risk factor for total mortality and cardiovascular disease: a study of men born in 1913. J Hypertens Suppl. 1993;11S81- S86
PubMed Link to Article
Pinsky  JLLeaverton  PEStokes III  J Predictors of good function: the Framingham Study. J Chron Dis. 1987;40 ((suppl 1)) 159S- 167S
Link to Article
Pinsky  JLBranch  LJJette  AM  et al.  Framingham Disability Study: relationship of disability to cardiovascular risk factors among persons free of diagnosed cardiovascular disease. Am J Epidemiol. 1985;122644- 656
PubMed
Reed  DMFoley  DJWhite  LRHeimovitz  HBurchfiel  CMMasaki  K Predictors of healthy aging in men with high life expectancies. Am J Public Health. 1998;881463- 1468
PubMed Link to Article
Visser  MLanglois  JGuralnik  JM  et al.  High body fatness, but not low fat-free mass, predicts disability in older men and women: the Cardiovascular Health Study. Am J Clin Nutr. 1998;68584- 590
PubMed
Hubert  HBBloch  DAOehlert  JWFries  JF Lifestyle habits and compression of morbidity. J Gerontol A Biol Sci Med Sci. 2002;57M347- M351
PubMed Link to Article
Centers for Disease Control and Prevention, Prevalence of adults with no known major risk factors for coronary heart disease—behavioral risk factor surveillance system, 1992. MMWR Morb Mortal Wkly Rep. 1994;4361- 6369
PubMed
American Heart Association, 2002 Heart and Stroke Statistical Update.  Dallas, Tex American Heart Association2001;
Schachter  FCohen  DKirkwood  T Prospects for the genetics of human longevity. Hum Genet. 1993;91519- 526
PubMed Link to Article
Benfante  RReed  DBrody  J Biological and social predictors of health in an aging cohort. J Chronic Dis. 1985;38385- 395
PubMed Link to Article
Cooper  RCutler  JADesvigne-Nickens  P  et al.  Trends and disparities in coronary heart disease, stroke, and other cardiovascular diseases in the United States: findings of the National Conference on Cardiovascular Disease Prevention. Circulation. 2000;1023137- 3147
PubMed Link to Article
Daviglus  MLStamler  J Major risk factors and coronary heart disease: much has been achieved but crucial challenges remain. J Am Coll Cardiol. 2001;381018- 1022
PubMed Link to Article
Manton  KGGu  X Changes in the prevalence of chronic disability in the United States black and non-black population above age 65 from 1982 to 1999. Proc Natl Acad Sci U S A. 2001;986354- 6359
PubMed Link to Article
Manton  KGCorder  LStallard  E Chronic disability trends in elderly United States populations: 1982-1994. Proc Natl Acad Sci U S A. 1997;942593- 2598
PubMed Link to Article
Freedman  VAMartin  LGSchoeni  RF Recent trends in disability and functioning among older adults in the United States: a systematic review. JAMA. 2002;2883137- 3146
PubMed Link to Article
Clarke  RBreeze  ESherliker  P  et al.  Design, objectives, and lessons from a pilot 25 year follow up re-survey of survivors in the Whitehall study of London Civil Servants. J Epidemiol Community Health. 1998;52364- 369
PubMed Link to Article
Ferraro  KFSu  YP Physician-evaluated and self-reported morbidity for predicting disability. Am J Public Health. 2000;90103- 108
PubMed Link to Article
Bergmann  MMByers  TFreedman  DSMokdad  A Validity of self-reported diagnoses leading to hospitalization: a comparison of self-reports with hospital records in a prospective study of American adults. Am J Epidemiol. 1998;147969- 977
PubMed Link to Article
Burt  VLWhelton  PRoccella  EJ  et al.  Prevalence of hypertension in the US adult population: results from the Third National Health and Nutrition Examination Survey, 1988-1991. Hypertension. 1995;25305- 313
PubMed Link to Article
The Hypertension Detection and Follow-up Program Cooperative Research Group, Mortality findings for stepped-care and referred-care participants in the Hypertension Detection and Follow-up Program, stratified by other risk factors. Prev Med. 1985;14312- 335
PubMed Link to Article

Figures

Place holder to copy figure label and caption
Figure 1.

Sample flowchart.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.

Multivariable-adjusted prevalence of favorable outcomes for 4 items in the 12-item Health Status Questionnaire (HSQ-12) at 26-year follow-up by baseline risk status (see asterisk footnote in Table 1 for definition of risk status) for 2564 women and 3409 men 65 years or older in 1996. Adjusted for age in 1996, race (indicator for African American), and baseline education (in years). The 4 items in the HSQ-12 are health perception: excellent or very good self-rated health; no limitation in walking several blocks (1 of the 3 physical functioning items); no or slight interference from physical or mental health in social functioning; feeling downhearted or blue none or a little of the time (1 of the 3 mental health items). Persons with a history of diagnosed diabetes, myocardial infarction, or any (minor or major) electrocardiographic abnormalities at baseline were excluded. P values for linear trend across 5 risk strata based on logistic regressions using "risk status" as an ordinal variable with values ranging from 1 to 5: for women, P<.001 for all except mental health (P = .02); for men, P<.001 for health perception and walking, P =.03 for social functioning, and P = .48 for mental health. RF indicates risk factor.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 3.

Multivariable-adjusted prevalence of self-reported coronary heart disease (CHD), cardiovascular disease (CVD), and any of 22 major diseases at 26-year follow-up by baseline risk status (see asterisk footnote in Table 1 for definition of risk status) for 2692 women and 3650 men 65 years or older. Adjusted for age in 1996, race (indicator for African American), and baseline education (in years). CHD includes myocardial infarction and angina; CVD, CHD, congestive heart failure, stroke, arteriosclerosis, and other heart diseases; and any disease, 6 groups of diseases in CVD, lung cancer, stomach cancer, intestinal cancer, rectal cancer, female cancers (breast cancer, ovarian cancer, and uterine cancer), prostate cancer, leukemia, other cancers excluding skin cancer, diabetes, pneumonia, emphysema, liver disease, kidney disease, Alzheimer disease, hip fracture, and other major diseases. P<.001 for linear trend across 5 risk strata for all outcomes for both men and women based on logistic regressions using "risk status" as an ordinal variable with values ranging from 1 to 5. RF indicates risk factor.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1. Baseline Characteristics of 2692 Women and 3650 Men 65 Years or Older in 1996 by Baseline Risk Status, Chicago Heart Association Detection Project in Industry Study, 1967-1973
Table Graphic Jump LocationTable 2. Multivariable-Adjusted Prevalence of Favorable Responses to 12 Items in the HSQ-12 Among 2692 Women and 3650 Men 65 Years or Older in 1996 by Baseline Risk Status, 1967-1973*
Table Graphic Jump LocationTable 3. Multivariable-Adjusted Mean Scores for 8 HSQ-12 Domains and Mean Summary Scores at 26-Year Follow-up According to Baseline Risk Status*

References

Stamler  JDaviglus  MLGarside  DBDyer  ARGreenland  PNeaton  JD Relationship of baseline serum cholesterol levels in 3 large cohorts of younger men to long-term coronary, cardiovascular, and all-cause mortality and to longevity. JAMA. 2000;284311- 318
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Miura  KDaviglus  MLDyer  AR  et al.  Relationship of blood pressure to 25-year mortality due to coronary heart disease, cardiovascular diseases, and all causes in young adult men: the Chicago Heart Association Detection Project in Industry. Arch Intern Med. 2001;1611501- 1508
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PubMed Link to Article
Schneider  ELBrody  JA Aging, natural death and the compression of morbidity: another view. N Engl J Med. 1983;309854- 856
PubMed Link to Article
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Stampfer  MJHu  FBManson  JERimm  EBWillett  WC Primary prevention of coronary heart disease in women through diet and lifestyle. N Engl J Med. 2000;34316- 22
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Daviglus  MLLiu  KGreenland  P  et al.  Benefit of a favorable cardiovascular risk-factor profile in middle age with respect to Medicare costs. N Engl J Med. 1998;3391122- 1129
PubMed Link to Article
Stamler  JRhomberg  PSchoenberger  JA  et al.  Multivariate analysis of the relationship of seven variables to blood pressure: findings of the Chicago Heart Association Detection Project in Industry, 1967-1972. J Chronic Dis. 1975;28527- 548
PubMed Link to Article
Levine  JBZak  B Automated determination of serum cholesterol. Clin Chim Acta. 1964;10381- 384
Link to Article
Prineas  RJCastle  CHCurb  JDHarrist  RLewin  AStamler  J Hypertension detection and follow-up program: baseline electrocardiographic characteristics of the hypertensive participants. Hypertension. 1983;5IV160- IV189
PubMed Link to Article
Chobanian  AVBakris  GLBlack  HR  et al. and the National High Blood Pressure Education Program Coordinating Committee, The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA. 2003;2892560- 2572
PubMed Link to Article
Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults, 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;2852486- 2497
PubMed Link to Article
Radosevitch  DPruitt  M Twelve-Item Health Status Questionnaire (HSQ-12) Version 2.0.  Bloomington, Minn Health Outcomes Institute1995;
Health Outcomes Institute, Twelve-Item Health Status Questionnaire (HSQ-12) Version 2.0 User Guide.  Bloomington, Minn Health Outcomes Institute1996;
Bowling  AWindsor  J Discriminative power of the Health Status Questionnaire 12 in relation to age, sex, and longstanding illness: findings from a survey of households in Great Britain. J Epidemiol Community Health. 1997;51564- 573
PubMed Link to Article
Pettit  TLivingston  GManela  MKitchen  GKatona  CBowling  A Validation and normative data of health status measures in older people: the Islington Study. Int J Geriatr Psychiatry. 2001;161061- 1070
PubMed Link to Article
Ware  JEKosinski  MKeller  SD A 12-item short-form health survey: construction of scales and preliminary tests of reliability and validity. Med Care. 1996;34220- 233
PubMed Link to Article
Liao  YLiu  KDyer  A  et al.  Major and minor electrocardiographic abnormalities and risk of death from coronary heart disease, cardiovascular diseases and all causes in men and women. J Am Coll Cardiol. 1988;121494- 1500
PubMed Link to Article
Lubitz  JBeebe  JBaker  C Longevity and Medicare expenditures. N Engl J Med. 1995;332999- 1003
PubMed Link to Article
Fries  JF Aging, natural death, and the compression of morbidity. N Engl J Med. 1980;303130- 135
PubMed Link to Article
Tibblin  GSvardsudd  KWelin  LErikson  HLarsson  B Quality of life as an outcome variable and a risk factor for total mortality and cardiovascular disease: a study of men born in 1913. J Hypertens Suppl. 1993;11S81- S86
PubMed Link to Article
Pinsky  JLLeaverton  PEStokes III  J Predictors of good function: the Framingham Study. J Chron Dis. 1987;40 ((suppl 1)) 159S- 167S
Link to Article
Pinsky  JLBranch  LJJette  AM  et al.  Framingham Disability Study: relationship of disability to cardiovascular risk factors among persons free of diagnosed cardiovascular disease. Am J Epidemiol. 1985;122644- 656
PubMed
Reed  DMFoley  DJWhite  LRHeimovitz  HBurchfiel  CMMasaki  K Predictors of healthy aging in men with high life expectancies. Am J Public Health. 1998;881463- 1468
PubMed Link to Article
Visser  MLanglois  JGuralnik  JM  et al.  High body fatness, but not low fat-free mass, predicts disability in older men and women: the Cardiovascular Health Study. Am J Clin Nutr. 1998;68584- 590
PubMed
Hubert  HBBloch  DAOehlert  JWFries  JF Lifestyle habits and compression of morbidity. J Gerontol A Biol Sci Med Sci. 2002;57M347- M351
PubMed Link to Article
Centers for Disease Control and Prevention, Prevalence of adults with no known major risk factors for coronary heart disease—behavioral risk factor surveillance system, 1992. MMWR Morb Mortal Wkly Rep. 1994;4361- 6369
PubMed
American Heart Association, 2002 Heart and Stroke Statistical Update.  Dallas, Tex American Heart Association2001;
Schachter  FCohen  DKirkwood  T Prospects for the genetics of human longevity. Hum Genet. 1993;91519- 526
PubMed Link to Article
Benfante  RReed  DBrody  J Biological and social predictors of health in an aging cohort. J Chronic Dis. 1985;38385- 395
PubMed Link to Article
Cooper  RCutler  JADesvigne-Nickens  P  et al.  Trends and disparities in coronary heart disease, stroke, and other cardiovascular diseases in the United States: findings of the National Conference on Cardiovascular Disease Prevention. Circulation. 2000;1023137- 3147
PubMed Link to Article
Daviglus  MLStamler  J Major risk factors and coronary heart disease: much has been achieved but crucial challenges remain. J Am Coll Cardiol. 2001;381018- 1022
PubMed Link to Article
Manton  KGGu  X Changes in the prevalence of chronic disability in the United States black and non-black population above age 65 from 1982 to 1999. Proc Natl Acad Sci U S A. 2001;986354- 6359
PubMed Link to Article
Manton  KGCorder  LStallard  E Chronic disability trends in elderly United States populations: 1982-1994. Proc Natl Acad Sci U S A. 1997;942593- 2598
PubMed Link to Article
Freedman  VAMartin  LGSchoeni  RF Recent trends in disability and functioning among older adults in the United States: a systematic review. JAMA. 2002;2883137- 3146
PubMed Link to Article
Clarke  RBreeze  ESherliker  P  et al.  Design, objectives, and lessons from a pilot 25 year follow up re-survey of survivors in the Whitehall study of London Civil Servants. J Epidemiol Community Health. 1998;52364- 369
PubMed Link to Article
Ferraro  KFSu  YP Physician-evaluated and self-reported morbidity for predicting disability. Am J Public Health. 2000;90103- 108
PubMed Link to Article
Bergmann  MMByers  TFreedman  DSMokdad  A Validity of self-reported diagnoses leading to hospitalization: a comparison of self-reports with hospital records in a prospective study of American adults. Am J Epidemiol. 1998;147969- 977
PubMed Link to Article
Burt  VLWhelton  PRoccella  EJ  et al.  Prevalence of hypertension in the US adult population: results from the Third National Health and Nutrition Examination Survey, 1988-1991. Hypertension. 1995;25305- 313
PubMed Link to Article
The Hypertension Detection and Follow-up Program Cooperative Research Group, Mortality findings for stepped-care and referred-care participants in the Hypertension Detection and Follow-up Program, stratified by other risk factors. Prev Med. 1985;14312- 335
PubMed Link to Article

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