Aging Clin. Exp. Res. 13: 95-104, 2001

Correlates of knowledge of one’s blood pressure and cholesterol levels among older members of a managed care plan N.T. Harawa1, H. Morgenstern1, J. Beck2, and A. Moore2 1Department of Epidemiology, School of Public Health, 2School of Medicine and Multicampus Program in Geriatric Medicine and Gerontology, University of California, Los Angeles, California, USA

ABSTRACT. We examined factors predicting knowledge of one’s blood pressure, total cholesterol, and high-density lipoprotein levels (HDL) among older persons who reported a recent blood pressure or cholesterol test. Data come from a self-administered, health risk assessment that was mailed to health plan members, age 55 and older, in a Santa Barbara, California medical group. Despite their universal access to health care and high levels of reported compliance with preventive health care screening practices, 41%, 49%, and 77% of respondents reported that they did not know their blood pressure, cholesterol, or HDL levels, respectively. After controlling for potential confounders, age and low income were inversely associated with the respondents’ ability to report each level. In addition, current smoking and obesity were inversely associated with self-reported knowledge of both cholesterol measures. Persons taking medication for hypertension or hypercholesterolemia were much more likely than those not taking medication to be able to report their blood pressure and cholesterol levels. Except for persons currently undergoing treatment for related conditions, these results suggest that a substantial proportion of the older persons at high risk for cardiovascular disease do not know their levels of these important biological risk factors. This lack of knowledge has important implications for public health education, and may hinder riskreduction efforts among the elderly. (Aging Clin. Exp. Res. 13: 95-104, 2001) ©2001,

Editrice Kurtis

INTRODUCTION Promoting active participation in one’s own health

care is one of the central goals of public health. Participation may include utilizing primary and secondary preventive health services, actively reducing risky behaviors, and taking up preventive practices. Increased awareness on the part of individuals of their personal risk factors for disease and injury often precedes these activities. Efforts to promote such awareness may be particularly important for elderly persons whose risk of death or disability is elevated, and for optimal management of chronic conditions such as hypertension and hypercholesterolemia. Blood pressure and cholesterol levels are important biological risk factors for cardiovascular and renal diseases (1, 2). Their significance is the frequent subject of televised news stories, and newspaper and magazine headlines. Home test kits that allow individuals to monitor themselves are now widely available (3), as are efforts to increase access to testing. In the United States, awareness and control of hypertension increased steadily between 1960 and 1991, but leveled off in the 1990s and still fell below year 2000 national health objectives (2, 4, 5). Results from National Heart, Lung, and Blood Institute phone surveys suggest similar trends for cholesterol screening and awareness since the surveys were initiated in 1983 (6). Included among the 1988 National Cholesterol Education Program goals were that all adults have their cholesterol measured at least once every five years, and that they know what their cholesterol level is (7). Studies indicate that the majority of elderly Americans do have their cholesterol (4) and blood pressure tested regularly (8), but we know little about the frequency with which they note and recall their personal values, or what factors predict such awareness. Only a few authors have investigated predictors

Key words: Cardiovascular disease, elderly, health education, health risk assessment. Correspondence: N.T. Harawa, M.P.H., Ph.D., 3669 Westwood Boulevard, #113, Los Angeles, CA 90034, USA. E-mail: [email protected] Received May 31, 2000; accepted in revised form December 5, 2000.

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Cholesterol and blood pressure knowledge

of awareness of hypertension (8) or hypercholesterolemia (10). Even fewer have examined whether patients actually know their own cholesterol level (4), and we could not find any previous studies that examined knowledge of one’s blood pressure level. The importance of knowing one’s blood pressure and cholesterol values has not been widely tested; however, some evidence indicates that an individual’s awareness and acceptance that he/she has hypertension or hypercholesterolemia positively influences his/her likelihood of taking steps to reduce disease risk (9-12). Because increases or decreases in blood pressure and cholesterol may reflect important life-style changes related to medication adherence, diet, salt intake, or aerobic activity (1, 2), this knowledge may reinforce the importance of proper health maintenance. Models for explaining health behaviors such as compliance with prescribed health services emphasize the roles of intention (13) and perceived threat in determining adoption of preventive health behaviors (14). For example, some individuals may not recall their blood pressure or cholesterol levels because they have no intention of altering these levels. This pattern would predict lower levels of knowledge among those who choose behaviors that increase their risk of cardiovascular disease, such as smokers and sedentary persons. Other individuals may not perceive any increased threat associated with their cholesterol or blood pressure levels because they do not understand the risk associated with hypertension and hypercholesterolemia, they have more imminent health concerns, or they have levels that fall within normal ranges. This would predict lower levels of knowledge among those of low socioeconomic status (particularly education), those who report serious health conditions, or those who do not report a history of a hypertension or hypercholesterolemia diagnosis. Individualized health education efforts have been associated with prescription refill compliance (15) and improved diet (16) among patients with chronic disease. Similarly, enhancing knowledge of cholesterol and blood pressure levels among patients may better motivate patients to follow doctors’ orders to fight the “silent killers” of hypertension and hypercholesterolemia. This may work in part by enhancing positive feedback. For example, a woman who begins a blood pressure-lowering drug regimen, and learns that her blood pressure has dropped from 165/110 mmHg to 150/100 mmHg may feel motivated to continue taking her medication as prescribed, even though she is still hypertensive. As one study demonstrated, hypertension control often presents a major challenge for patients and doctors (17); this investi-

gation of workers with optimal access to regular health care found that hypertension control was achieved among only 12% of hypertensives. The exploratory analyses for this paper were performed on a portion of a larger dataset resulting from the pilot testing of a health-risk-assessment instrument designed for individuals over age 54 (called the UCLA Senior Health Profile). The pilot study involved recruitment from two California sites and one national sample (see 18 for further details). The subjects analyzed in this paper came from one of the three sites, and were members of a Santa Barbara medical group practice. Our objectives were: 1) to determine, among those participants who recently had a cholesterol or blood pressure test, the proportion who were able to report their blood pressure, total serum cholesterol, and high-density lipoprotein (HDL) levels; 2) to identify determinates of this knowledge among persons over age 54; and 3) to use this information to hypothesize about why specific variations in the distribution of knowledge exist among older persons. SUBJECTS AND METHODS Three thousand nine hundred sixty-two (3962) Santa Barbara third-party payer enrollees, age 55 or older, in the Santa Barbara Medical Foundation were mailed invitations to complete the UCLA Senior Health Profile (mailing lists for the mailed questionnaire were obtained from the Santa Barbara Medical Foundation). All those returning the pre-paid postcard after a single invitation were mailed health risk assessment for the elderly (HRA-E). Of the 1073 (27%) persons who returned the postcard invitation, 710 (66%) returned the HRA-E questionnaire. Sixteen (2.3%) of these returned questionnaires were incomplete or otherwise unusable, leaving 393 female and 301 male respondents (694 total). We did not have data on non-responders; however, we compared the HRA-E respondents to the distribution of Santa Barbara County residents in the 1990 US Census. Respondents were very similar to residents, aged 55 and older, in their distributions by age and sex. They were more educated than were county residents over the age of 24 (e.g., 79% vs 59% had >12 years’ education), and reported higher levels of family/household income than did residents over the age of 54 (e.g., 24% vs 15% reported incomes of ≥$75 000) (19). These census income data are not corrected for inflation. Because the focus of this investigation was to identify predictors of knowledge, not utilization or access to care, the analyses in this paper are limited to

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HRA-E participants who reported having been tested for the specific risk-factor level within the reference period. This period was the previous 12 months for blood pressure, and the previous 5 years for cholesterol. Participants were not asked about the type of cholesterol check that they had received during the previous 5 years (i.e., total cholesterol or cholesterol/lipid breakdown), so it was impossible to determine which participants had actually had their HDL levels measured. We assume that both tests were generally performed at the same time as the National Cholesterol Education Program recommends (2). The questionnaire involved 17 principal domains covering physical activity and functioning, injury prevention, hearing and vision, preventive health care, medication use, medical history, nutrition, alcohol and tobacco use, psychosocial health, social networks, occupational status, physical signs and symptoms, demographic information, and self-reported physical health measurements and status. The vast majority of items required answering simple yes/no or multiple choice questions. The assessment took an average of 43 minutes to complete. Details of the HRA-E instrument and its development are discussed elsewhere (18). The outcome measures are based on answers to three questions about the respondents’ systolic and diastolic blood pressure, total cholesterol, and HDL cholesterol levels. For each question, respondents were given the option of providing the given measurement or checking a box indicating that they did not know it or were not sure. We classified those providing a numeric answer as “knowing” the measure, and compared them with those who did not. Participants leaving both choices blank were considered missing for all analyses. Statistical analysis All data analyses were completed in SAS for Windows version 6.08 (SAS Institute, Cary, NC). Logistic regression models were fit to the data using a modified backward selection approach. Variables for categories of age (55-69, 70-79, 80-89, 90+), gender, annual family income (<$15 000; $15-$75 000; and ≥$75 000), and memory status (positive vs negative indication of perceptual or imaginal memory impairment) (20) were forced into all models when estimating the effects of other covariates. A variable indicating whether or not the individual was taking any blood pressure or cholesterol-lowering medication was also forced in the model predicting knowledge of the respective measure. The decision to force variables for these five predictors into the models was based on published findings indicating that the predictor was re-

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lated to health knowledge or to preventive health behaviors that can lower hypertension and hypercholesterolemia (4, 16, 17, 21). Crude and adjusted odds ratios (OR) and 95% confidence intervals (CI) were derived from the model results to estimate the association between each predictor and reported knowledge of each biological risk factor. Other potential predictors were then considered for inclusion in each model using backward selection with a p-value criterion of 0.2 for remaining in the model. Stepwise selection was also employed for the sake of comparison, and resulted in the selection of the same covariates in each model. The predictors considered included current marital status (married vs single), race/Hispanic origin (white/non-Hispanics vs Hispanics and non-whites), smoking status, physical activity level [based on the Physical Activity Scale for the Elderly or PASE score (22)], body mass index (kg/m2), education (<12, 12, >12 years completed), hearing and vision status, indication of functional impairment [based on instrumental (IADL) (23, 24), advanced (AADL) (25), and basic activities of daily living scales (ADL) (24)], current problem drinking (as indicated by average consumption of 14 or more drinks per week and responses to the CAGE (26) or Short MAST-G scales (27), current depression [as indicated by the Mental Health Index-Five or MHI-5 (28)], and self-reported history of clinical depression, other emotional or mental illnesses, and glaucoma. Various cardiovascular-related conditions were also considered, including a reported history of high blood pressure, congestive heart failure, coronary artery disease, irregular heartbeat, stroke, and diabetes. Appropriate cut-off levels for the continuous and categorical predictors (age, income, education, physical impairment, and PASE) were chosen by examining the crude dose-response relations between each factor and reported knowledge. RESULTS The HRA-E respondents reported high levels of cholesterol and blood pressure testing. The vast majority reported a blood pressure check within one year (97%), and a cholesterol check within 5 years (94%) of completing the Health Profile. A substantial proportion of the population was currently taking blood pressure (28%) or cholesterol-lowering (11%) medications. Thirty-four percent (34%) reported that they had been diagnosed with hypertension at some point in their lives. The questionnaire did not ask respondents about history of a hypercholesterolemia diagnosis. Of those who knew the given measure, 27% indicated blood pressure levels of 140/90 mmHg

Cholesterol and blood pressure knowledge

or higher, 60% reported cholesterol levels above 240 mg/dL, and 9% reported HDL levels below 35 mg/dL (Table 1). Table 2 shows the percentages of the HRA-E respondents who reported numeric values for blood pressure, total cholesterol, and HDL by categories of selected predictors among those who had taken a cholesterol or blood pressure test within the reference period. Fifty-nine percent, 51%, and 23% of these participants knew their blood pressure, total cholesterol, and HDL levels, respectively. The proportion not answering any one of these questions did not exceed 4%. In order to evaluate whether the inability to report blood pressure or cholesterol levels related primarily to the quantitative aspects of these measures, we examined the respondents’ ability to report their height and weight. Only 3 (0.4%) respondents did not report their weight; 26 (3.7%) did not report their height. Of those respondents who did not report their height, 67%, 58%, and 23% reported their blood pressure, total cholesterol, and HDL levels, respectively. Table 3 shows crude and adjusted results for the regression of blood pressure knowledge on several predictors selected by the modified backwards procedure described above. When the five covariates were forced into the model, only having a medical history of congestive heart failure (vs no history of the disease) was sufficiently predictive of the outcome to warrant inclusion in the model (adjusted OR=0.52, 95%

CI=0.20-1.41). Males were more likely to know their blood pressure than females (adjusted OR=1.54, 95% CI=1.06-2.17). Age was inversely associated with knowledge under age 90, but this association reversed in the oldest age category. Nevertheless, the odds ratio for age ≥90 vs <70 is imprecisely estimated (adjusted OR=1.10, 95% CI=0.18-6.75). As expected, income was positively associated with knowledge. Not surprisingly, taking hypertensive medication substantially increased one’s odds of knowing his/her blood pressure, and having indications of memory problems decreased this odds; however, the latter association was fairly weak (adjusted OR=0.67, 95% CI=0.32-1.37). Results for knowledge of one’s total cholesterol were somewhat similar to those found for blood pressure (Table 4). Males were more likely to know their levels than females, and knowledge had an inverse association with age, while income had a positive one. Nevertheless, the association with gender was weaker (adjusted OR=1.26, 95% CI=0.84-1.88), the inverse association with age held across all age groups, and only those in the lowest income group (<$15 000/year) reported less knowledge. Persons with memory problems did not differ from those screening negative for them. Higher levels of knowledge were found among those with moderate to high levels of physical activity than among those with sedentary to low activity levels. Smokers, obese respondents (BMI>30 kg/m2), and respondents with im-

Table 1 - Number (%) of Santa Barbara Medical Foundation respondents, aged 55+, who utilized hypertension- and hypercholesterolemia-related health services and self-reported blood pressure and cholesterol levels (total N=694). Questionnaire item Blood pressure measurement in the last year? Has a physician ever told you that you have high blood pressure? Are you now taking medicine for high blood pressure? Reported blood pressure (mmHg)a normal <130/80 high-normal 130-139 systolic or 85-89 diastolic hypertension ≥140/90 Cholesterol measurement in the last five years? Are you now taking medicine for high cholesterol? Total cholesterol (mg/dL)b desirable <200 borderline high 200-240 high >240 High-density lipoprotein (HDL) cholesterol (mg/dL)b low <35 normal ≥35

No. (%) of those providing an answer 670 (97) 235 (34) 197 (28) 172 (43) 201 (50) 27 (6.8) 645 (94) 72 (11) 134 (40) 125 (38) 71 (22) 13 (9.0) 131 (91)

a

Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure 1997 recommendations for classifying blood pressure in adults not on anti-hypertensive medication and without an acute illness. b National Cholesterol Education Program 1994 guidelines for classifying cholesterol and HDL level.

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Table 2 - Percent of Santa Barbara Medical Foundation respondents, aged 55+, who reported values for their blood pressure, total cholesterol, and high-density lipoprotein (HDL) levels, among subjects who were tested in the past year (blood pressure) or five (cholesterol) years. Percent of population who reported knowing their... Predictor category Gender Male Female Age in years 55-69 70-79 80-89 90+ Years of education <12 12 >12 Annual family income <$15 000 $15-74 999 ≥$75 000 Screen for impaired memory Positive Negative Body mass index (kg/m2) ≤30 >30 Current smoking status Smoker Non-smoker Total population aNumber

Number

Blood pressure (N=660a)

Total cholesterol (N=634a)

HDL cholesterol (N=623a)

301 393

64 55

57 47

24 22

376 224 86 8

61 58 53 62

55 47 43 20

25 22 17 0

28 121 543

38 58 61

18 41 55

8.7 18 25

45 444 148

45 58 67

33 53 54

14 23 24

47 642

47 60

50 51

18 23

619 48

59 57

52 39

24 7

34 654

45 60

29 52

7 23

694

59

51

23

of respondents with non-missing answers for knowledge of level.

paired physical functioning were less likely to know their total cholesterol measures than were non-smokers and persons who were not obese or impaired. A number of clinical factors also predicted cholesterol knowledge. As expected, those taking medication for hypercholesterolemia were much more likely to report their cholesterol values than were those not taking such medications (adjusted OR=2.11, 95% CI=1.08-4.11). A history of coronary heart disease, arrhythmia, or glaucoma was positively associated with knowledge, while a history of diabetes or mental illness other than depression was inversely associated with it. Table 5 shows the results for predicting knowledge of one’s HDL level. The results for age and income are similar to those found for total cholesterol. Males appear somewhat less likely to know their HDL levels than females, as are persons with memory

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problems; however, 95% CI for both estimates are quite wide. Obesity and smoking are again both inversely associated with knowledge, and these associations are stronger than were found for total cholesterol. The positive association between taking cholesterol-lowering medication and knowledge is weaker. Persons with a history of coronary heart disease or glaucoma have approximately double the odds of knowing their HDL levels, as do persons without each disease. DISCUSSION Blood pressure, serum cholesterol, and HDL levels have been shown to predict a number of cardiovascular sequelae in older persons (1, 2). Demographic factors and clinical variables predict reported knowl-

Cholesterol and blood pressure knowledge

edge of these three biological risk factors for cardiovascular disease in this population of older persons who have a regular source of primary care, and who were recently tested. Subjects whose demographic, medical, and smoking profile indicated increased risk for such negative outcomes were often less likely than subjects with a lower risk profile to be aware of their levels. For example, persons with congestive heart failure were less likely to know their blood pressure and total cholesterol level, and current smokers and obese persons were less likely to know their total or HDL cholesterol level. In addition, age was inversely associated with knowledge of all three measures. The vast majority of respondents reported their weight and height, indicating that failure to report blood pressure and cholesterol levels was not simply related to the quantitative nature of these values. Interestingly, blood pressure had a fairly strong relation with gender, with males more likely than females to know their blood pressure levels. A similar but weaker trend was seen for total cholesterol but not for HDL level. Our findings differ from other studies that found either no gender differences in awareness (29), or that females were more likely than males to be aware of their hypertension (17, 30). Considering that after menopause risk of heart disease and stroke for women becomes similar to that of men (2), and that women generally use health care more frequently than men do (31), these findings were surprising and warrant further study. One recent study has even indicated that blood pressure and cholesterol may be more predictive of elderly women’s ischemic heart disease risk than men’s (32).

Perhaps as interesting as the positive results above are the negative findings in these data. Memory impairment appeared to have only a weak effect on selfreported knowledge. This may be because only 47 persons indicated memory impairment, and the memory screen itself lacked specificity, including persons with very slight memory loss. It is unlikely that demented persons would have responded to our questionnaire. Neither a history of diagnosed depression nor an indication of current depression appeared to be important predictors. Furthermore, current problem drinking, an indication of hearing or vision problems, and marital status also were not selected into any of our prediction models because their associations with knowledge were small. An association was observed between level of physical activity and knowledge of total cholesterol, but not knowledge of blood pressure or HDL levels. Others have found education to be a strong predictor of similar outcomes such as awareness of hypercholesterolemia (4), functional health literacy among hypertensives and diabetics (21), and urinary-incontinence knowledge among persons 65 and older (33). In these data, annual family income was a more important predictor. We found a strong, crude (unadjusted) association between increasing grade level completed and knowledge, but control for family income essentially eliminated any estimated education effects. We did not find any race associations in this population, perhaps because of the small number of non-white participants. Other investigators have found hypertensive blacks to be

Table 3 - Crude and adjusteda odds ratios (OR) [and 95% confidence intervals (CI)] predicting knowledge of one’s blood pressure (N=670),b by level of selected predictors: Logistic regression analyses. Predictor aMale

(vs female) (<70 years) 70-79 years 80-89 years 90+ years aTotal family income (vs≥$75 000/year) <$15 000/year $15-74 999/year aPositive (vs negative) screen indicative of memory problems aCurrently taking medicine for high blood pressure (vs not taking medicine) Medical history (vs no history) of congestive heart failure

Crude OR (95% CI)

Adjusteda OR (95% CI)

1.44 (1.05-1.97)

1.54 (1.06-2.17)

0.88 (0.63-1.25) 0.72 (0.44-1.17) 1.06 (0.25-4.50)

0.80 (0.54-1.17) 0.76 (0.43-1.32) 1.10 (0.18-6.75)

0.40 (0.20-0.81) 0.68 (0.46-1.02)

0.43 (0.20-0.93) 0.69 (0.46-1.05)

0.58 (0.32-1.06)

0.67 (0.32-1.37)

2.09 (1.45-3.00)

2.07 (1.38-3.11)

0.75 (0.30-1.88)

0.52 (0.20-1.41)

aAge

aResults bAmong

are adjusted for all variables shown. Based on a priori information, variables for the first six predictors were forced into the regression model. Santa Barbara Medical Foundation, respondents aged 55+ who had had their blood pressure taken within the previous 12 months.

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Table 4 - Crude and adjusteda odds ratios (OR) [and 95% confidence intervals (CI)] predicting knowledge of one’s total cholesterol level (N=645),b by level of selected predictors: Logistic regression analyses. Predictor aMale

(vs female) (vs <70 years) 70-79 years 80-89 years 90+ years aTotal family income (vs ≥$75 000/year) <$15 000/year $15-74 999/year aPositive (vs negative) screen indicative of impaired memory aCurrently taking medicine for high cholesterol (vs not taking medicine) Physical Activity Scale for the Elderly (PASE) (vs very high physical activity) sedentary to low moderate to high Impaired physical functioning (vs none) Body Mass Index >30 kg/m2 (vs ≤30 kg/m2) Current smoker (vs current non-smoker) Personal medical history (vs no history) of: congestive heart failure coronary heart disease irregular heart beat diabetes emotional/mental illness other than depression glaucoma

Crude OR (95% CI)

Adjusteda OR (95% CI)

1.48 (1.08-2.03)

1.26 (0.84-1.88)

0.72 (0.51-1.02) 0.60 (0.36-1.01) 0.20 (0.02-1.82)

0.72 (0.47-1.13) 0.57 (0.27-1.19) 0.14 (0.01-1.80)

0.43 (0.20-0.92) 0.98 (0.66-1.43) 0.96 (0.50-1.84)

0.40 (0.15-1.11) 1.21 (0.78-1.88) 1.07 (0.44-2.58)

2.44 (1.42-4.18)

2.11 (1.08-4.11)

0.96 (0.59-1.56) 1.31 (0.92-1.88) 0.59 (0.42-0.82) 0.49 (0.21-1.12) 0.34 (0.12-1.00)

1.34 (0.70-2.56) 1.71 (1.10-2.65) 0.57 (0.36-0.92) 0.60 (0.28-1.28) 0.42 (0.16-1.13)

0.31 (0.10-0.96) 1.19 (0.70-2.03) 1.32 (0.91-1.91) 0.86 (0.47-1.60) 0.47 (0.17-1.26) 1.02 (0.59-1.77)

0.34 (0.08-1.52) 1.96 (0.80-4.81) 1.53 (0.94-2.48) 0.42 (0.19-0.96) 0.22 (0.04-1.12) 2.20 (1.01-4.79)

aAge

a b

Results are adjusted for all variables shown. Based on a priori information, variables for the first six predictors were forced into the regression model. Among Santa Barbara Medical Foundation, respondents aged 55+ who had their cholesterol taken within the previous 5 years.

aware of their condition more often than hypertensive whites (17), but less likely to know their cholesterol level (4). A few study limitations should be considered when making inferences from these results. Medical records were not examined to determine the accuracy of the self-reported blood pressure and cholesterol levels; however, at least one study indicates that the correlation between actual and self-reported cholesterol levels is quite high (Pearson’s r=0.85) (16). Furthermore, the survey did not directly assess whether those who reported their levels could correctly interpret their implications for disease risk. Potential sources of systematic error also exist. Bias may have arisen from inaccurate responses due to poor recall or failure to understand the questions. The overall response rate was low, making inferences to the larger population of health plan members difficult. Responders were more educated and affluent than other Santa Barbara residents. Finally, for some of the findings discussed, the number of study subjects was too small to yield precise estimates or to provide suf-

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ficient statistical power to adequately test relations between knowledge and certain predictors. CONCLUSIONS The results presented here were obtained from cross-sectional data collected from a self-selected population. Although such study design limitations restrict causal inferences and generalizations to other populations, some important conclusions and suggestions for future research can be made. First, despite the generally health-conscious and affluent nature of the sample as well as a history of recent testing, almost half of the respondents could not report values for their blood pressure and total cholesterol. Less than one quarter could report their HDL levels. Second, these findings fall below current public health goals. For example, Healthy People 2000 objectives are that 90% of adults have had a blood pressure test in the past two years, and can state whether it was normal or high (34). The National Cholesterol Education Program’s goal is 100% testing and knowledge

Cholesterol and blood pressure knowledge

of total cholesterol levels among US adults (7). Third, knowledge of these risk factors for stroke and heart disease is likely to be even lower in the population as a whole. For comparison, annual National Heart, Lung, and Blood Institute phone surveys indicate that less than 40% of the general public can report their cholesterol levels (6) vs approximately 50% of the HRA-E respondents. Fourth, some subgroups at elevated risk for cardiovascular disease were less likely to report their numerical risk factor values than were those at lower risk. For example, the proportion of persons who could report their cholesterol level was higher in most subgroups examined than in the general population (6); however, among obese persons, smokers, those over 90, and those with low incomes or less than high school education, cholesterol knowledge was substantially lower. Further studies are needed to replicate these findings in other populations, to determine how persons 55 and older interpret their blood pressure and cholesterol values, and to evaluate the role of health care providers in promoting this awareness. By looking at predictors of blood pressure and cholesterol knowledge, we explored a question that has been dealt with minimally in the literature. This knowledge may be a useful marker for otherwise poorly defined aspects of a patient’s self-involvement in preventive health such as motivation, perceived treatment need, and proper comprehension of doc-

tors’ orders. For example, lack of awareness of cholesterol or blood pressure levels among obese persons, smokers, those with low incomes, and persons with certain underlying clinical conditions may indicate a general reluctance to take preventive health action. For others in these risk groups, such lack of awareness may signal a knowledge gap that, when filled, will increase intentions to initiate or maintain risk-reducing activities. It is likely that a significant portion of our study population falls into this second group, and may benefit from increased knowledge as their completion and return of an extensive health risk assessment indicate a desire to increase their awareness, and to consider changes in their health habits. Physicians, medical assistant staff, and health educators should be encouraged to make older patients aware of their blood pressure and cholesterol levels, particularly those patients with other risk factors for cardiovascular or renal disease. Feedback from health risk assessments such as the one examined here should also encourage respondents to learn their blood pressure and cholesterol levels, and educate them on how to properly interpret what these levels mean. Given incomplete knowledge levels in the population, such assessments should be supplemented with blood pressure and cholesterol information from the medical chart, as this information is critical to providing an adequate health assessment and proper feedback to participants. Further research into these disparities

Table 5 - Crude and adjusteda odds ratios (OR) [and 95% confidence intervals (CI)] predicting knowledge of one’s high-density lipoprotein level (N=645),b by level of selected predictors: Logistic regression analyses. Predictor aMale

(vs female) (vs<70 years) 70-79 years 80-89 years 90+ years aTotal family income (vs ≥$75 000/year) <$15 000/year $15-74 999/year aPositive (vs negative) screen indicative for impaired memory aCurrently taking medicine for high cholesterol (vs not taking the medicine) Body Mass Index >30 kg/m2 (vs ≤30 kg/m2) Current smoker (vs current non-smoker) Personal medical history includes (vs does not include): Coronary heart disease Glaucoma

Crude OR (95% CI)

Adjusteda OR (95% CI)

1.17 (0.80-1.71)

0.79 (0.50-1.24)

0.89 (0.60-1.35) 0.63 (0.32-1.24) c

0.84 (0.52-1.35) 0.43 (0.18-1.03) c

0.52 (0.19-1.46) 0.98 (0.62-1.56) 0.75 (0.32-1.74)

0.27 (0.06-1.24) 1.09 (0.66-1.79) 0.56 (0.18-1.73)

2.15 (1.27-3.66) 0.24 (0.07-0.78) 0.26 (0.06-1.13)

1.43 (0.74-2.76) 0.28 (0.08-0.95) 0.26 (0.06-1.18)

1.72 (0.96-3.09) 1.19 (0.63-2.25)

2.01 (0.94-4.30) 1.90 (0.88-4.07)

aAge

a b c

Results are adjusted for all variables shown. Based on a priori information, variables for the first six predictors were forced into the regression model. Among Santa Barbara Medical Foundation, respondents aged 55+ who had their cholesterol taken within the previous 5 years. Numbers too small to fit model.

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N.T. Harawa, H. Morgenstern, J. Beck, et al.

in knowledge may improve management of hypercholesterolemia and hypertension, and inform the development of behavior-modification programs for reducing disease risk in elderly populations. ACKNOWLEDGEMENTS This study was funded by grants from the John A. Hartford Foundation, the California Wellness Foundation, and the Health Care Financing Administration, Cooperative Agreement 17-C90300/9-01. J. Higa was responsible for study coordination. K. Knight and E. Zimmerman provided substantial assistance in the project.

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