Background
Cardiovascular disease (CVD) is the leading cause of death in adults with diabetes mellitus (DM). Counseling by physicians is effective in inducing lifestyle modification.
Objective
To determine the prevalence of modifiable CVD risk factors and counseling by physicians among adults with DM.
Methods
Data on 9496 adults with DM and 150 493 adults without DM from the 1999 Behavioral Risk Factor Surveillance System were analyzed to yield estimates of CVD risk factors and counseling by physicians during routine visits. Multiple logistic regression was used to adjust estimates for age, sex, ethnicity, education, and income. Population estimates were created using software for the statistical analysis of correlated data (SUDAAN) because of the complex survey design of the Behavioral Risk Factor Surveillance System.
Results
Diabetes mellitus was more prevalent in adults aged 55 and older and in blacks and Hispanic or other ethnicities (both P<.001). Modifiable CVD risk factors, such as hypertension (56% vs 22%), high cholesterol (41% vs 20%), obesity (78% vs 57%), and insufficient physical activity (66% vs 56%), were more prevalent in adults with DM (all P<.001) and differed by ethnicity, sex, and age. Counseling about weight loss (50% vs 21%, P<.001), smoking cessation (78% vs 67%, P = .01), eating less fat (78% vs 71%, P<.001), and increasing physical activity (67% vs 36%, P<.001) was less than ideal in both groups and did not change after adjusting for age, sex, ethnicity, education, and income with multiple logistic regression.
Conclusions
Although adults with DM have a high prevalence of modifiable CVD risk factors, counseling by physicians about lifestyle modification is less than optimal. There is a need to improve patient counseling for lifestyle modification by primary care physicians.
DIABETES MELLITUS (DM) is prevalent in the United States. About 10.5 million persons had a diagnosis of DM in 1999, and about 800 000 new diagnoses are made each year.1 Diabetes is associated with significant morbidity and mortality, and the economic burden of DM to the individual and to society is substantial, including direct costs and indirect costs, such as disability, work loss, and premature mortality.1-3
Cardiovascular disease (CVD) is the leading cause of death in persons with DM. Persons with DM have a 2- to 4-fold increased risk of death from CVD than adults in the general population of similar age. In addition, CVD accounts for 48% of deaths among persons with DM4,5 and is listed as the cause of death in about 65% of persons with DM.6 Once patients with DM develop CVD, the prognosis worsens, compared with persons without DM,7-12 and the cost of care increases dramatically.13,14
Although there are several recognized CVD risk factors, strategies to reduce the risk of CVD focus on controlling hypertension, high cholesterol, obesity, smoking, and sedentary lifestyle, because they are amenable to lifestyle modification. Because more than 70% of adults with DM receive routine care in primary care settings,15 primary care physicians are particularly well suited to provide counseling about lifestyle modification. Consequently, the US Preventive Services Task Force,16 American Heart Association,17 and American Diabetes Association18 recommend counseling about modifiable CVD risk factors during preventive health examinations in primary care.
To determine the prevalence of modifiable CVD risk factors among adults with DM and the prevalence of counseling by physicians about such risk factors, we analyzed data from the 1999 Behavioral Risk Factor Surveillance System (BRFSS).19
Research methods and design
This is a cross-sectional study of data on adults with DM obtained from the 1999 BRFSS. The BRFSS is a state-based, random-digit dialing telephone survey of the noninstitutionalized, civilian population of the United States aged 18 and older. Details about the BRFSS survey and methods have been published previously.20-22
Our sample included only individuals who responded to specific BRFSS questions. "Yes" responses were coded as one group, while "no," "not sure," "don't know," or "refused to answer" were combined into another group. Individuals who had no responses coded ("missing" or "skipped") were excluded from our analysis. In 1999, there were 9496 adults with diagnosed DM, based on self-report that a physician had told them they had DM. We excluded persons who reported a diagnosis of DM during pregnancy. We defined modifiable CVD risk factors as the presence of hypertension, high cholesterol, obesity, smoking, or insufficient physical activity. Our definition of modifiable CVD risk factors is consistent with that used in previous studies.23-27
Hypertension and high cholesterol groups were each derived from respondents who reported ever having been told by a physician that they had high blood pressure or high cholesterol. The obesity category was derived from the respondents' body mass index (BMI) and was defined as weight in kilograms divided by the square of height in meters. We based our classification of overweight and obesity on the recommendation by the National Heart, Lung, and Blood Institute in 1998.28 According to this classification, a BMI less than 18.5 is classified as underweight, 18.5 to 24.9 as normal weight, and 25.0 to 29.9 as overweight. Further classifications include obesity 1 (BMI, 30.0-34.9), obesity 2 (BMI, 35.0-39.9), and extreme obesity (BMI, ≥40.0). For the analysis, we used 4 weight categories: normal weight (BMI, 18.5-24.9), overweight (BMI, 25.0-29.9), obesity (BMI, 30.0-39.9), and extreme obesity (BMI, ≥40.0).
Current smoking was defined as individuals who reported having smoked 100 cigarettes in their lifetime and who smoked currently. Insufficient physical activity was defined as individuals who reported having no leisure-time physical activity or physical activity less than 20 minutes 3 or more times per week. Education was defined as the highest grade or year of school completed, and income was defined as the annual household income from all sources. The physician checkup group was derived from respondents who reported seeing a physician for a routine checkup within the past year (1-12 months previously).
Opportunity for counseling was present if an individual reported having a checkup by a physician within the previous 12 months. Counseling was said to have occurred if during the previous 12 months an individual reported that a physician or other health care professional talked to them about weight loss, exercise, eating foods with less fat or cholesterol, or quitting smoking. Missed opportunity for counseling about modifiable CVD risk factors was defined as the absence of counseling in an individual with CVD risk factors who reported having a physician checkup within the previous 12 months.
Three ethnic groups (white, black, and Hispanic or other) and 3 age categories (18-34, 35-54, and ≥55 years) were used for the analysis. Two categories of income (<$25 000 and ≥$25 000), based on federal poverty levels, and 2 categories of education (less than high school and high school education or higher) were determined.
We performed 3 levels of statistical analyses. First, the prevalence of CVD risk factors was compared between adults with and without DM. Second, the prevalence of CVD risk factors was determined among persons with DM by ethnicity, sex, and age. To determine the prevalence of counseling by physicians for modifiable CVD risk factors, the denominator consisted of the number of persons with each CVD risk factor seen by a physician in the previous year.
For example, opportunity for counseling for smoking cessation was determined among smokers who reported having at least one physician checkup in the previous 12 months. Similarly, among persons who had a checkup, opportunities for counseling about weight loss were among persons with overweight and obesity, counseling about eating less fat among persons with high cholesterol, and counseling about regular physical activity among all adults. This resulted in different sample sizes for the different CVD risk factors.
Third, we compared the prevalence of counseling for modifiable CVD risk between adults with and without DM. Multiple logistic regression was used to control for age, sex, ethnicity, education, and income for counseling by physicians about CVD risk factors to obtain adjusted prevalence. Because of the complex sampling design of the BRFSS, commercially available software (SAS29 and SUDAAN30) was used for statistical analyses to obtain variance estimates. The weighting factor in BRFSS pr oduces national estimates by accounting for differences of sampling in geographic regions, telephone density, number of telephones in a household, number of adults in a household, selected cluster size, and distribution of age, sex, and ethnicity in the selected population of the sampling states.19
Table 1 compares the baseline characteristics of adults with and without DM. Women constituted 52% of both groups (P = .93). There were higher percentages of blacks and Hispanic or other ethnicities in the DM group compared with the group without DM, and there were higher percentages of adults aged 55 and older in the DM group (both P<.001). Likewise, the percentage of persons with less than a high school education (59% vs 46%) and a household income less than $25 000 (58% vs 42%) was higher among adults with DM compared with adults without DM (both P<.001).
Comparing modifiable CVD risk factors between groups with and without DM, the prevalence of self-reported insufficient physical activity was high in both groups, but was higher among persons with DM (66% vs 56%, P<.001). Similarly, the prevalence of hypertension (56% vs 22%), high cholesterol (41% vs 20%), and overweight and obesity (78% vs 57%) was higher among adults with DM compared with adults without DM (all P<.001). Conversely, the prevalence of smoking was higher in adults without DM (23% vs 15%, P<.001).
Table 2 compares the prevalence of modifiable CVD risk factors by ethnicity, sex, and age among adults with DM. Hypertension was more prevalent in blacks, followed by whites and Hispanic or other ethnicities (64% vs 56% vs 50%, P<.001). Overweight and obesity were more prevalent in blacks and Hispanic or other ethnicities and less prevalent in whites (84% vs 78% vs 77%, P = .002). The prevalence of smoking (15% vs 19% vs 15%, P = .07), high cholesterol (42% vs 42% vs 38%, P = .26), and insufficient physical activity (66% vs 61% vs 73%, P = .27) was not significantly different across the 3 ethnic groups.
Comparing risk factors by sex, the prevalence of hypertension (59% vs 53%, P<.001) and high cholesterol (43% vs 39%, P = .01) was higher in women than in men. Although men and women had similar overweight and obesity prevalence (79% vs 78%), women were more likely to have extreme obesity with a BMI of 40 or higher (16% vs 6%, P<.001). The prevalence of insufficient physical activity and smoking did not differ significantly by sex.
Comparing CVD risk factors across age groups (Table 2), the prevalence of hypertension (27% vs 49% vs 62%) and high cholesterol (17% vs 40% vs 44%) increased with increasing age (both P<.001). The prevalence of insufficient physical activity did not differ significantly (77% vs 61% vs 67%, P = .13), while overweight and obesity (77% vs 83% vs 77%, P<.001) differed across the 3 age groups in an unpredictable manner. In contrast, the prevalence of smoking decreased with increasing age (29% vs 23% vs 11%, P<.001).
A comparison of the prevalence of counseling for modifiable CVD risk factors in adults with and without DM is shown in Table 3. Among adults with a BMI of 25 or higher who reported having a physician checkup within the previous year, 50% of adults with DM reported receiving counseling from a health care professional about weight loss, compared with 21% in adults without DM. Similarly, among adults who reported having a physician checkup who also had modifiable CVD risk factors, such as smoking, physical inactivity, or high cholesterol, the prevalence of counseling was less than optimal. Adults with DM were more likely to receive counseling about increasing physical activity (67% vs 36%, P<.001), smoking cessation (78% vs 67%, P = .01), and eating foods with less fat (78% vs 71%, P<.001) compared with adults without DM. After adjusting for the effects of age, sex, ethnicity, education, and income by multiple logistic regression, the differences observed between adults with and without DM remained.
Adults with DM were more likely to have modifiable CVD risk factors compared with adults without DM, and these risk factors differed by ethnicity, sex, and age. There were missed opportunities for counseling about lifestyle modification among at-risk patients, which needs improvement in primary care settings. This is the first study, to our knowledge, that has identified the prevalence of modifiable CVD risk factors and counseling by primary care providers for these risk factors among adults with DM in the United States.
The distributions of ethnicity, sex, and age among adults with DM in this study are consistent with those of previous studies on DM.1,24,25,31 The finding of a higher prevalence of modifiable CVD risk factors among persons with DM is not surprising. The clustering in certain individuals of DM, hypertension, high cholesterol, and obesity, known as the metabolic cardiovascular syndrome32 or the deadly quartet,33 has been described. In fact, a recent article26 put DM alongside other major risk factors as an important cause of CVD for a similar reason.
In this study, the prevalence of overweight and obesity, insufficient physical activity, cigarette smoking, hypertension, and high cholesterol is similar to the findings reported by the Centers for Disease Control and Prevention, based on data from the 1997 BRFSS.34 In our study, the prevalence of overweight and obesity in persons without DM was 57%, compared with 54% in the general population in the 1997 study. The prevalence of cigarette smoking (23% vs 23%), hypertension (22% vs 24%), and high cholesterol (20% vs 29%) followed the same pattern.34
On the contrary, the prevalence of insufficient physical activity (56%) differed from that reported in 1997 (28%).34 A likely explanation for the difference is the definition of physical inactivity used in the years of comparison. The calculation for physical inactivity in 1997 was based on the percentage of adults who did not engage in any leisure-time physical activity other than regular job duties.22,34 In contrast, physical inactivity in 1999 was defined as individuals who reported having no leisure-time physical activity or who had physical activity less than 20 minutes 3 or more times per week.19 The 1999 definition is more likely to increase the percentage of insufficient physical activity among adults in the United States than the 1997 definition used for the estimates by Holtzman and colleagues.34
Data reported by the Centers for Disease Control and Prevention in 199635 on state-specific prevalence of participation in physical activity were close to our estimates. The definition of insufficient physical activity used in that study was similar to the definition in our study, and 64% to 84% (median, 73%) of respondents reported no leisure-time activity or irregular activity. Therefore, our estimate on insufficient physical activity in the US population appears to be reliable.
The findings from this study suggest that primary care physicians are doing a less than optimal job in counseling patients about lifestyle modification for CVD risk factors, particularly in those at high risk. Counseling efforts in primary care were less than ideal in patients with and without DM. These findings are concerning because they indicate that, despite the evidence that each modifiable CVD risk factor is independently associated with heart disease and mortality, physicians are not acting in a consistent manner. The evidence is established for hypertension,36,37 high cholesterol,38-40 cigarette smoking,41-48 physical activity,49-52 and obesity.53,54
There is also evidence to support the efficacy of counseling by physicians in modifying CVD risk behavior, including smoking cessation,55-58 physical activity,59-62 and healthy diets,63,64 leading to the recommendations published by the US Preventive Services Task Force,16 American Heart Association,17 and American Diabetes Association.18 Consequently, it is unclear why the prevalence of counseling remains less than optimal in primary care settings.
This is not the only study that has documented low levels of counseling by physicians for CVD risk factors. A recent study65 on physician advice about CVD risk reduction in 7 US states and Puerto Rico showed that only 42% of persons surveyed reported receiving a physician's advice to avoid high-fat or high-cholesterol foods. About the same percentage reported receiving advice to exercise more. Those with a history of heart attack, myocardial infarction, angina, coronary heart disease, or stroke were more likely to report receiving a physician's advice to eat less fat and exercise more. Although estimates of counseling in this study differ from those in that study, the pattern of increased counseling for patients at higher risk is similar.
Primary care physicians have mentioned several reasons for the low prevalence of counseling, including not having adequate time to provide counseling, having limited training in counseling techniques, and being doubtful about the effectiveness of their counseling efforts.66-72 These reasons may partly explain the low prevalence of counseling of patients with DM observed in this study.
There are 3 limitations to this study. First, because the data were based on self-report, there is the potential for recall bias, especially regarding counseling about CVD risk factors by physicians. This is less likely to apply to this study because previous studies73-76 have shown that self-reported information on DM, CVD risk factors, and health promotion habits is reliable.
However, what constitutes adequate counseling remains unclear. The US Preventive Services Task Force16 distinguishes physician counseling from physician advice, and defines physician counseling as a more interactive and in-depth encounter, as opposed to physician advice, which may involve a brief recommendation to adopt or modify a behavior. Also, whether patients considered referral to weight loss centers, smoking cessation programs, or counseling during DM education programs as counseling by their physician cannot be determined in this study.
Second, because the BRFSS is a telephone-based survey, households without telephones were excluded. This may bias our estimates to a certain degree. The extent of such bias is likely to be minimal for 2 reasons. First, telephone coverage for households was high in the United States in 1999, ranging from 89% to 99%.19 Second, several studies76-79 on the reliability and validity of the telephone survey in the BRFSS compared with in-person or household interviews have shown that the estimates obtained by both methods are similar for most of the population.
Third, because the BRFSS is limited to civilian and noninstitutionalized adults, generalization can only be made to that segment of the population covered by the survey.
There are 2 major implications of our study. First, there is the need for primary care physicians to recognize the prevalence of modifiable CVD risk factors among adults with DM. Recognizing the pattern in which these CVD risk factors cluster in persons with DM may improve identification of high-risk patients. In addition, physicians can use data from this study to stratify patients with DM during routine office visits, as recommended by the American Heart Association.26,27 Second, although there is evidence to support counseling by physicians—and several guidelines and recommendations encourage counseling about modifiable CVD risk factors—primary care physicians appear to be performing at less than optimal levels. This may suggest that strategies to improve counseling techniques in primary care are needed, especially on how to counsel patients to modify high-risk behavior. There may be benefit in incorporating counseling skills into medical residency education or as continuing medical education activity for primary care physicians.
Although adults with DM have a high prevalence of modifiable CVD risk factors, counseling by physicians about lifestyle modification is less than optimal. There is a need to improve patient counseling for lifestyle modification by primary care physicians.
Accepted for publication June 6, 2001.
This study was supported in part by grants 1K08HS11418-01 and 1 P01-HS10871-01 from the Agency for Health Care Research and Quality, Rockville, Md (Dr Egede), and grant U50/CCU417281-02 from the Centers for Disease Control and Prevention, Atlanta, Ga (Drs Egede and Zheng).
The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the Agency for Healthcare Research and Quality or the Centers for Disease Control and Prevention.
Corresponding author and reprints: Leonard E. Egede, MD, Division of General Internal Medicine and Geriatrics, Department of Medicine, Medical University of South Carolina, McClennan-Banks Adult Primary Care Clinic, Fourth Floor, 326 Calhoun St, PO Box 250100, Charleston, SC 29425.
2.American Diabetes Association, Economic consequences of diabetes mellitus in the U.S. in 1997.
Diabetes Care. 1998;21296- 309
Google ScholarCrossref 3.Selby
JVRay
GTZhang
DColby
CJ Excess costs of medical care for patients with diabetes in a managed care population.
Diabetes Care. 1997;201396- 1402
Google ScholarCrossref 4.Centers for Disease Control and Prevention, The Prevention and Treatment of Complications of Diabetes Mellitus: A Guide for Primary Care Practitioners. Atlanta, Ga Public Health Service, US Dept of Health and Human Services1991;
5.Centers for Disease Control and Prevention, Diabetes Surveillance, 1993. Atlanta, Ga Public Health Service, US Dept of Health and Human Services1993;
6.Geiss
LSHerman
WHSmith
PJ Mortality in non–insulin dependent diabetes mellitus.
National Diabetes Data Group Diabetes in America2nd ed. Bethesda Md National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health1995;233- 258NIH publication 95-1468
Google Scholar 7.Smith
JWMarcus
FISerokman
R Prognosis of patients with diabetes mellitus after acute myocardial infarction.
Am J Cardiol. 1984;54718- 721
Google ScholarCrossref 8.Abbott
RDDonahue
RPKannel
WBWilson
PW The impact of diabetes on survival following myocardial infarction in men vs women: the Framingham Study.
JAMA. 1988;2603456- 3460
Google ScholarCrossref 9.Singer
DEMoulton
AWNathan
DM Diabetic myocardial infarction: interaction of diabetes with other preinfarction risk factors.
Diabetes. 1989;38350- 357
Google ScholarCrossref 10.Stone
PHMuller
JEHartwell
T
et al. for the MILIS Study Group, The effect of diabetes mellitus on prognosis and serial left ventricular function after acute myocardial infarction: contribution of both coronary disease and diastolic left ventricular dysfunction to the adverse prognosis.
J Am Coll Cardiol. 1989;1449- 57
Google ScholarCrossref 11.Miettinen
HLehto
SSalomaa
V
et al. for the FINMONICA Myocardial Infarction Register Study Group, Impact of diabetes on mortality after the first myocardial infarction.
Diabetes Care. 1998;2169- 75
Google ScholarCrossref 12.Not Available, Diabetes mellitus: a major risk factor for cardiovascular disease: a joint editorial statement by the American Diabetes Association; the National Heart Lung, and Blood Institute; the Juvenile Diabetes Foundation; the National Institute of Diabetes and Digestive and Kidney Diseases; and the American Heart Association.
Circulation. 1999;1001132- 1133
Google ScholarCrossref 13.Krop
JSPowe
NRWeller
WEShaffer
TJSaudek
CDAnderson
GF Patterns of expenditures and use of services among older adults with diabetes: implications for the transition to capitated managed care.
Diabetes Care. 1998;21747- 752
Google ScholarCrossref 14.Smith
TLMelfi
CAKesterson
JASandmann
BJKotsanos
JG Direct medical charges associated with myocardial infarction in patients with and without diabetes.
Med Care. 1999;37
((suppl 4))
AS4- AS11
Google Scholar 15.Harris
MI Medical care for patients with diabetes: epidemiologic aspects.
Ann Intern Med. 1996;124117- 122
Google ScholarCrossref 16.U.S. Preventive Services Task Force, Guide to Clinical Preventive Services. 2nd ed. Baltimore, Md Williams & Wilkins1996;
17.Not Available, 1999 Heart and Stroke Statistical Update. Dallas, Tex American Heart Association1998;
18.American Diabetes Association, Standards of medical care for patients with diabetes mellitus: clinical practice recommendations 2001.
Diabetes Care. 2001;24
((suppl 1))
S33- S43
Google ScholarCrossref 19.Centers for Disease Control and Prevention, Behavioral Risk Factor Surveillance System 1999 Survey Data [BSB CD-ROM, series 1, No. 5]. Atlanta, Ga National Center for Chronic Disease Prevention and Health Promotion, US Dept of Health and Human Services1999;
20.Remington
PLSmith
MYWilliamson
DFAnda
RFGentry
EMHogelin
GC Design, characteristics, and usefulness of state-based behavioral risk factor surveillance: 1981-87.
Public Health Rep. 1988;103366- 375
Google Scholar 21.Centers for Disease Control and Prevention, Behavioral Risk Factor Surveillance System User's Guide. Atlanta, Ga US Dept of Health and Human Services1998;
22.Holtzman
DPowell-Griner
EBolen
JCRhodes
L State- and sex-specific prevalence of selected characteristics: behavioral risk factor surveillance system, 1996 and 1997.
MMWR Morb Mortal Wkly Rep. 2000;49
((SS-6))
1- 39
Google Scholar 23.Not Available, Prevalence of adults with known major risk factors for coronary heart disease: Behavioral Risk Factor Surveillance System, 1992.
MMWR Morb Mortal Wkly Rep. 1994;4361- 69
Google Scholar 24.Not Available, Cardiovascular disease risk factors and related preventive health practices among adults with and without diabetes: Utah, 1988-1993.
MMWR Morb Mortal Wkly Rep. 1995;44805- 809
Google Scholar 25.Not Available, Prevalence of cardiovascular disease risk-factor clustering among persons aged ≥45 years: Louisiana, 1991-1995.
MMWR Morb Mortal Wkly Rep. 1997;46585- 588
Google Scholar 26.Grundy
SMBenjamin
IJBurke
GL
et al. Diabetes and cardiovascular disease: a statement for healthcare professionals from the American Heart Association.
Circulation. 1999;1001134- 1146
Google ScholarCrossref 27.Smith
SC
JrGreenland
PGrundy
SMfor the American Heart Association, AHA conference proceedings: prevention conference, V: beyond secondary prevention: identifying the high-risk patient for primary prevention: executive summary.
Circulation. 2000;101111- 116
Google ScholarCrossref 28.Not Available, Clinical Guidelines on the Identification, Evaluation, and Treatment of Overweight and Obesity in Adults. Bethesda, Md National Heart, Lung, and Blood Institute, National Institutes of Health1998;NIH publication 98-4083.
29.Not Available, SAS [computer program]. Version 8.0. Cary, NC SAS Institute1999;
30.Shah
BV Software for Survey Data Analysis (SUDAAN) [computer program]. Version 7.51. Research Triangle Park, NC Research Triangle Institute1990;
31.Lindeman
RDRomero
LJHundley
R
et al. Prevalences of type 2 diabetes, the insulin resistance syndrome, and coronary heart disease in an elderly, biethnic population.
Diabetes Care. 1998;21959- 966
Google ScholarCrossref 32.Arnesen
H Introduction: the metabolic cardiovascular syndrome.
J Cardiovasc Pharmacol. 1992;20
((suppl 8))
S1- S4
Google Scholar 33.Kaplan
NM The deadly quartet: upper-body obesity, glucose intolerance, hypertriglyceridemia, and hypertension.
Arch Intern Med. 1989;1491514- 1520
Google ScholarCrossref 34.Holtzman
DPowell-Griner
EBolen
JCRhodes
L State- and sex-specific prevalence of selected characteristics: Behavioral Risk Factor Surveillance System, 1996 and 1997.
MMWR Morb Mortal Wkly Rep. 2000;49
((SS-6))
1- 14
Google Scholar 35.Centers for Disease Control and Prevention, State-specific prevalence of participation in physical activity: Behavioral Risk Factor Surveillance System, 1994.
MMWR Morb Mortal Wkly Rep. 1996;45673- 675
Google Scholar 36.UK Prospective Diabetes Study Group, Cost effectiveness analysis of improved blood pressure control in hypertensive patients with type 2 diabetes: UKPDS 40.
BMJ. 1998;317720- 726
Google ScholarCrossref 37.UK Prospective Diabetes Study Group, Tight blood pressure control and risk of macrovascular and microvascular complications in type 2 diabetes: UKPDS 38.
BMJ. 1998;317703- 713
Google ScholarCrossref 38.Pyorala
KPedersen
TRKjekshus
JFaergeman
OOlsson
AGThorgeirsson
G Cholesterol lowering with simvastatin improves prognosis of diabetic patients with coronary heart disease: a subgroup analysis of the Scandinavian Simvastatin Survival Study (4S).
Diabetes Care. 1997;20614- 620
Google ScholarCrossref 39.Haffner
SMAlexander
CMCook
TJ
et al. Reduced coronary events in simvastatin-treated patients with coronary heart disease and diabetes or impaired fasting glucose levels: subgroup analyses in the Scandinavian Simvastatin Survival Study.
Arch Intern Med. 1999;1592661- 2667
Google ScholarCrossref 40.Jonsson
BCook
JRPedersen
TR The cost-effectiveness of lipid lowering in patients with diabetes: results from the 4S trial.
Diabetologia. 1999;421293- 1301
Google ScholarCrossref 41.Gay
ECCai
YGale
SM
et al. Smokers with IDDM experience excess morbidity: the Colorado IDDM Registry.
Diabetes Care. 1992;15947- 952
Google ScholarCrossref 42.Rimm
EBChan
JStampfer
MJColditz
GAWillett
WC Prospective study of cigarette smoking, alcohol use, and the risk of diabetes in men.
BMJ. 1995;310555- 559
Google ScholarCrossref 43.Chaturvedi
NStephenson
JMFuller
JH The relationship between smoking and microvascular complications in the EURODIAB IDDM Complications Study.
Diabetes Care. 1995;18785- 792
Google ScholarCrossref 44.Wei
MMitchell
BDHaffner
SMStern
MP
et al. for the San Antonio Heart Study, Effects of cigarette smoking, diabetes, high cholesterol, and hypertension on all-cause mortality and cardiovascular disease mortality in Mexican Americans.
Am J Epidemiol. 1996;1441058- 1065
Google ScholarCrossref 45.Poulsen
PLEbbehoj
EHansen
KWMogensen
CE Effects of smoking on 24-h ambulatory blood pressure and autonomic function in normoalbuminuric insulin-dependent diabetes mellitus patients.
Am J Hypertens. 1998;111093- 1099
Google ScholarCrossref 46.Mehler
PSJeffers
BWBiggerstaff
SLSchrier
RW Smoking as a risk factor for nephropathy in non–insulin-dependent diabetics.
J Gen Intern Med. 1998;13842- 845
Google ScholarCrossref 47.Turner
RCMillns
HNeil
HA
et al. Risk factors for coronary artery disease in non–insulin dependent diabetes mellitus: United Kingdom Prospective Diabetes Study (UKPDS: 23).
BMJ. 1998;316823- 828
Google ScholarCrossref 48.Persson
PGCarlsson
SSvanstrom
LOstenson
CGEfendic
SGrill
V Cigarette smoking, oral moist snuff use and glucose intolerance.
J Intern Med. 2000;248103- 110
Google ScholarCrossref 49.Burchfiel
CMSharp
DSCurb
JD
et al. Physical activity and incidence of diabetes: the Honolulu Heart Program.
Am J Epidemiol. 1995;141360- 368
Google ScholarCrossref 50.Haapanen
NMiilunpalo
SVuori
IOja
PPasanen
M Association of leisure time physical activity with the risk of coronary heart disease, hypertension and diabetes in middle-aged men and women.
Int J Epidemiol. 1997;26739- 747
Google ScholarCrossref 51.Hu
FBSigal
RJRich-Edwards
JW
et al. Walking compared with vigorous physical activity and risk of type 2 diabetes in women: a prospective study.
JAMA. 1999;2821433- 1439
Google ScholarCrossref 52.Folsom
ARKushi
LHHong
CP Physical activity and incident diabetes mellitus in postmenopausal women.
Am J Public Health. 2000;90134- 138
Google ScholarCrossref 53.Morisaki
NKawano
MWatanabe
SSaito
YYoshida
S Role of obesity in development of ischemic heart disease in elderly diabetic patients.
Gerontology. 1992;38167- 173
Google ScholarCrossref 54.Wannamethee
SGShaper
AG Weight change and duration of overweight and obesity in the incidence of type 2 diabetes.
Diabetes Care. 1999;221266- 1272
Google ScholarCrossref 55.Wilson
DMTaylor
DWGilbert
JR
et al. A randomized trial of a family physician intervention for smoking cessation.
JAMA. 1988;2601570- 1574
Google ScholarCrossref 56.Kottke
TEBattista
RNDeFriese
GHBrekke
ML Attributes of successful smoking cessation interventions in medical practice: a meta-analysis of 39 controlled trials.
JAMA. 1988;2592883- 2889
Google ScholarCrossref 57.Bronson
DLFlynn
BSSolomon
LJVacek
PSecker-Walker
RH Smoking cessation counseling during periodic health examinations.
Arch Intern Med. 1989;1491653- 1656
Google ScholarCrossref 58.Ockene
JKKristeller
JGoldberg
R
et al. Increasing the efficacy of physician-delivered smoking interventions: a randomized clinical trial.
J Gen Intern Med. 1991;61- 8
Google ScholarCrossref 59.Harris
SSCaspersen
CJDeFriese
GHEstes
EH
Jr Physical activity counseling for healthy adults as a primary preventive intervention in the clinical setting: report for the US Preventive Services Task Force.
JAMA. 1989;2613588- 3598
Google ScholarCrossref 61.Calfas
KJLong
BJSallis
JFWooten
WJPratt
MPatrick
K A controlled trial of physician counseling to promote the adoption of physical activity.
Prev Med. 1996;25225- 233
Google ScholarCrossref 62.Long
BJCalfas
KJWooten
W
et al. A multisite field test of the acceptability of physical activity counseling in primary care: project PACE.
Am J Prev Med. 1996;1273- 81
Google Scholar 63.Ockene
ISHebert
JROckene
JKMerriam
PAHurley
TGSaperia
GM Effect of training and a structured office practice on physician-delivered nutrition counseling: the Worcester-Area Trial for Counseling in Hyperlipidemia (WATCH).
Am J Prev Med. 1996;12252- 258
Google Scholar 64.Evans
ATRogers
LQPeden
JG
Jr
et al. for the CADRE Study Group, Teaching dietary counseling skills to residents: patient and physician outcomes.
Am J Prev Med. 1996;12259- 265
Google Scholar 65.Not Available, Physician advice and individual behaviors about cardiovascular disease risk reduction: seven states and Puerto Rico, 1997.
MMWR Morb Mortal Wkly Rep. 1999;4874- 77
Google Scholar 66.Wechsler
HLevine
SIdelson
RKRohman
MTaylor
JO The physician's role in health promotion: a survey of primary-care practitioners.
N Engl J Med. 1983;30897- 100
Google ScholarCrossref 67.Orleans
CTGeorge
LKHoupt
JLBrodie
KH Health promotion in primary care: a survey of U.S. family practitioners.
Prev Med. 1985;14636- 647
Google ScholarCrossref 69.Valente
CMSobal
JMuncie
HL
JrLevine
DMAntlitz
AM Health promotion: physicians' beliefs, attitudes, and practices.
Am J Prev Med. 1986;282- 88
Google Scholar 70.Henry
RCOgle
KSSnellman
LA Preventive medicine: physician practices, beliefs, and perceived barriers for implementation.
Fam Med. 1987;19110- 113
Google Scholar 71.Ammerman
ASDeVellis
RFCarey
TS
et al. Physician-based diet counseling for cholesterol reduction: current practices, determinants, and strategies for improvement.
Prev Med. 1993;2296- 109
Google ScholarCrossref 72.Kushner
RF Barriers to providing nutrition counseling by physicians: a survey of primary care practitioners.
Prev Med. 1995;24546- 552
Google ScholarCrossref 73.Shea
SStein
ADLantigua
RBasch
CE Reliability of the behavioral risk factor survey in a triethnic population.
Am J Epidemiol. 1991;133489- 500
Google Scholar 74.Stein
ADLederman
RIShea
S The Behavioral Risk Factor Surveillance System questionnaire: its reliability in a statewide sample.
Am J Public Health. 1993;831768- 1772
Google ScholarCrossref 75.Brownson
RCJackson-Thompson
JWilkerson
JCKiani
F Reliability of information on chronic disease risk factors collected in the Missouri Behavioral Risk Factor Surveillance System.
Epidemiology. 1994;5545- 549
Google Scholar 76.Bowlin
SJMorrill
BDNafziger
ANLewis
CPearson
TA Reliability and changes in validity of self-reported cardiovascular disease risk factors using dual response: the behavioral risk factor survey.
J Clin Epidemiol. 1996;49511- 517
Google ScholarCrossref 77.Gentry
EMKalsbeek
WDHogelin
GC
et al. The behavioral risk factor surveys, II: design, methods, and estimates from combined state data.
Am J Prev Med. 1985;19- 14
Google Scholar 78.Jackson
CJatulis
DEFortmann
SP The Behavioral Risk Factor Survey and the Stanford Five-City Project Survey: a comparison of cardiovascular risk behavior estimates.
Am J Public Health. 1992;82412- 416
Google ScholarCrossref 79.Serdula
MCoates
RByers
T
et al. Evaluation of a brief telephone questionnaire to estimate fruit and vegetable consumption in diverse study populations.
Epidemiology. 1993;4455- 463
Google ScholarCrossref