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Physician advice and support for physical activity
Physician Advice and Support for Physical Activity Results from a National Survey Russell E. Glasgow, PhD, Elizabeth G. Eakin, PhD, Edwin B. Fisher, PhD, Stephen J. Bacak, MS, Ross C. Brownson, PhD Background: It is increasingly well documented that physical activity (PA) is a key preventive behavior and that visits to a physician provide an important opportunity for advice and counseling. This paper reports on physician counseling behaviors regarding PA and other chronic disease risk factors from a national survey. Methods:
A diverse sample of U.S. adults (N⫽1818), with oversampling of lower-income households, was surveyed about their PA level as well as a host of social, environmental, and physician counseling issues.
Results:
Overall, 28% of respondents reported receiving physician advice to increase their PA level. Of those who received advice, only 38% received help formulating a specific activity plan and 42% received follow-up support. Patients who received advice and support were more likely to be older, nonwhite, and to have more chronic illnesses and more contact with their doctor.
Conclusions: Physician advice, counseling, and follow-up are important components of the socialenvironmental supports needed to increase population PA levels. Health system changes, including teaching communication skills, prompts to use those skills, and system changes to support attention to PA, are needed to extend promotion of PA to more patients. Medical Subject Headings (MeSH): counseling; exercise, health promotion; physician– patient relations (Am J Prev Med 2001;21(3):189 –196) © 2001 American Journal of Preventive Medicine
R
egular physical activity (PA) is essential for disease prevention and health promotion.1– 4 Regular PA reduces the risk of diabetes, colon cancer, hypertension, and obesity.1 Physical inactivity is an independent heart disease risk factor of similar magnitude (relative risk of 1.9) to smoking, hypertension, and hypercholesterolemia.5 PA promotes psychological well-being, and builds and maintains healthy bones, muscles, and joints, thus reducing the risk of falls in the elderly and increasing functional independence.1 PA is also an important part of the self-care regimen for many chronic illnesses.6 In 1990, approximately 300,000 deaths were attributed to physical inactivity and poor nutrition, while 400,000 deaths were
From the AMC Cancer Research Center, Center for Behavioral and Community Studies (Glasgow, Eakin), Denver, Colorado; Queensland University of Technology (Eakin), Kelvin Grove, Queensland, Australia; Division of Health Behavior Research and Department of Psychology (Fisher), Washington University, St. Louis, Missouri; and Department of Community Health and Prevention Research Center, School of Public Health, St. Louis University (Bacak, Brownson), St. Louis, Missouri Address correspondence and reprint requests to: Russell E. Glasgow, PhD, AMC Cancer Research Center, Center for Behavioral and Community Studies, 1600 Pierce Street, Denver, CO 80214. E-mail: [email protected].
attributed to tobacco.5,7 Sedentary behavior has been estimated to cost the United States $5.7 billion annually.7 National recommendations on PA from the American College of Sports Medicine (ACSM) and the Centers for Disease Control and Prevention (CDC) state that all adults should accumulate 30 minutes a day of moderate-intensity activity on five or more days of the week. However, national survey data indicate that approximately 68% of U.S. adults do not achieve this recommended level.5 Among special populations, such as the poor and underserved, older adults, and those with chronic illness, there is even greater need for attention to PA.1,8,9 A recent study of 771 older adult patients from an urban primary healthcare center serving low-income patients revealed that only 10% met the ACSM/CDC guidelines for regular moderate PA.10 In addition to facing the common barriers to PA (e.g., lack of time, lack of support, and lack of interest), members of these special populations face additional challenges, making the initiation and maintenance of PA even more difficult. These challenges include unsafe or unappealing environmental conditions, lack of community or neighborhood resources, and lack of money or transportation. Additional barriers faced by
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those with chronic illness, which are disproportionately prevalent among minority and low-income populations, include pain and discomfort as well as psychological barriers, such as depression, and beliefs that those with chronic illness should not exercise.10 –12 A visit to a primary healthcare provider appears to be an opportune time for PA counseling, especially due to the fact that the majority of adults see their healthcare providers three or more times a year.13 Numerous studies have evaluated the outcomes of primary care– based PA interventions.14,15 The national health promotion and disease prevention objectives in Healthy People 201016 and by the U.S. Preventive Services Task Force17 recommend that physicians and other healthcare providers counsel their patients to be physically active as part of routine healthcare visits, yet the majority of physicians do not do so. Previous studies of older adults found that between 22% to 48% reported having received advice regarding PA from their physician.18,19 Finally, recent studies based on patients who reported recent medical checkups suggest that 34% of patients received physician advice to exercise20 and 56% of patients were questioned about exercise.21 Both studies20,21 indicated that patients with higher income levels were more likely to have PA discussed. The main purposes of this paper are threefold: (1) to report on patient recall of interactions with primary care physicians regarding PA and other preventive behaviors; (2) to study a large and more representative sample than most previous research, including a sizable proportion of low-income and minority respondents, to allow investigation of the relationship of these factors to PA counseling; and (3) to examine relationships between more intensive components of PA counseling (e.g., activity planning and follow-up) and patient characteristics. Information related to purposes 2 and 3 has not been reported previously and was obtained from a national survey that included an oversampling of lowerincome individuals.
Methods Sampling Data were collected via telephone survey, using a modified version of the sampling plan of the Behavioral Risk Factor Surveillance System (BRFSS). The primary objective of the overall survey was to obtain representative data among varied populations across the United States on patterns and determinants of PA. There were no financial or other incentives to respondents, and the survey methods have been described in detail elsewhere.22–24 The cross-sectional risk factor survey used a random-digit-dialing technique to collect data.25 To obtain a representative sample of lower-income individuals, ZIP codes were oversampled that had ⱖ32% of residents below the federal poverty level. Once the ZIP codes were selected, the area code/exchange combinations that were at least 70% within the ZIP code defined area were determined and used as the final sample frame for this stratum. The
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random-digit-dialing sample that was used for this project can be best characterized as a single-stage epsem (equal probability selection method) sample of all residential telephone numbers (listed, unlisted, and unpublished numbers) in the defined sample frame. The system used a database consisting of all residential telephone exchanges, working phone bank information, and various geographic variables, such as state, county, and zip code. On a national basis, this definition covers an estimated 96.4% of all residential telephone numbers and 99.96% of listed residential numbers. The sample frame consisted of the set of all area code/exchange combinations and their associated working banks, which met the criteria listed above. The result was that every potential telephone number within the defined sample frame had a known and equal probability of selection. During interviews, if contact could not be made after three attempts, another number was selected from the primary sampling unit.
Instrumentation and Data Collection The survey instrument was developed using a combination of questions from the BRFSS, the National Health Interview Survey, and other recent surveys.22,23,26 –31 When valid and reliable scales were documented in the literature and available, every effort was made to use these with the scale intact. In a few cases, adaptations were made from in-person to telephone administration (e.g., asking a “yes/no” question rather than a checklist that would be used in an in-person interview). The final instrument contained a total of 90 questions, including skip patterns, with an average administration time of 30 minutes. An initial set of questions asked about an individual’s access to health care (e.g., “Do you have any kind of healthcare coverage, including health insurance, prepaid plans such as HMOs, or government plans such as Medicare, Medicaid, or Veteran’s care?”). Additional questions focused on health professional advice for various preventive behaviors (i.e., PA, fruit and vegetable consumption, weight reduction, dietary fat reduction). These questions were included to compare results on PA advice to those in other health promotion areas. For persons who had received PA advice, further questions— modeled on the “4 A’s” counseling approach (Ask, Advise, Assist, and Arrange Follow-up) recommended by the National Cancer Institute32—were asked specifically about developing a plan for exercise and follow-up from a provider on subsequent visits. Specific questions were: (1) “Have you ever been advised within the last year by a doctor or other health professional to exercise more?” (Yes/No); (2) “Has your doctor or healthcare provider helped you to develop a plan to increase your exercise?” (Yes/No); (3) “Has your doctor or healthcare provider followed up with you at subsequent visits to see how you were doing to increase your exercise?” (Yes/No). Newly developed questions on PA behavior focused on moderate and vigorous PA in the domains of occupational PA, time spent in non-occupational walking, moderate-intensity recreational activities, and vigorous-intensity recreational activities. These questions are designed to estimate compliance with new public health recommendations4 and have been previously tested for reliability and validity.33 Between September 1999 and January 2000, interviews were completed for 1818 men and women (Table 1). Experienced
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Table 1. Frequency of physicians’ advice within various sociodemographic and medical characteristic subgroups among participants in U.S. Physical Activity Study, 1999 –2000 (N⫽1818)
Characteristic Gender Female Male Missing Age 18–29 30–44 45–64 65⫹ Missing Race/ethnicity White Black/African-American Other Missing Education ⬍High school (HS) HS graduate or some post HS College grad Post grad or professional degree Missing Income, $c ⬍10K 10K–⬍20K 20K–⬍50K ⱖ50K Missing Doctor for regular health care Yes No Missing # of doctor visits per year 0–1 2–3 4⫹ Missing Type of insurance HMO PPO or point of service Traditional None Missing Marital status Married or member of unmarried couple Divorced, widowed, separated, never married Missing # of chronic illnesses 0 1–2 3⫹ Missing
a
a
More exerciseb
Eat more fruits and vegetablesb
Reduce fatb (diet)
Reduce Quit stressb smokingc
Number
Percentage
1220 598 0
67.1 32.9 0
31.7 21.6
35.9 25.4
30.9 25.1
34.5 24.3
74.3 67.8
487 548 479 295 9
26.8 30.1 26.3 16.2 0.5
22.0 26.1 35.7 31.3
32.0 26.6 33.8 41.5
19.1 25.7 36.7 38.2
30.2 32.8 33.4 25.5
64.8 73.8 73.0 82.8
971 546 295 6
53.4 30.0 16.2 0.4
24.1 34.8 30.8
23.1 46.2 38.6
23.6 37.7 30.5
28.4 34.1 35.3
71.1 76.9 68.5
330 1068 301 118 1
18.2 58.7 16.6 6.5 0.1
33.0 28.5 24.7 24.6
44.5 32.7 23.7 19.5
37.0 28.4 24.7 22.9
33.0 31.0 32.3 23.7
73.0 73.1 70.0 50.0
347 378 610 283 200
19.1 20.8 33.6 15.6 11.0
34.0 25.9 28.1 26.9
43.2 36.0 28.7 22.6
32.6 29.2 30.0 23.7
34.0 32.8 30.6 27.9
77.4 76.2 65.9 71.7
1397 421 0
76.8 23.2 0
31.6 17.6
35.4 22.9
32.4 17.6
34.0 21.7
78.9 53.7
376 542 526 374
20.7 29.8 28.9 20.6
24.5 27.3 40.9
26.9 31.5 44.9
21.3 30.6 41.0
22.1 31.4 44.3
70.4 73.6 84.6
421 473 511 360 53
23.2 26.0 28.1 19.8 2.9
28.5 29.7 29.7 5.0
34.7 30.3 34.1 31.4
27.3 29.9 32.3 26.1
32.8 30.1 34.5 26.9
80.0 73.5 73.8 63.5
884
48.6
29.1
30.2
28.4
30.3
71.0
931
51.2
27.7
34.6
29.5
32.0
72.7
3
0.2
830 686 289 13
45.7 37.7 15.9 0.7
16.7 32.8 50.9
21.9 35.1 56.1
15.3 32.8 58.7
20.4 35.8 50.5
59.5 79.6 85.9
a
Number and percentage in entire population. Percentage of respondents answering “yes” to advice questions. c Percentage, for current cigarette smokers only (n⫽393). b
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interviewers conducted the interviews, and each interviewer underwent at least 16 hours of training. The response rate was calculated according to the Council of American Survey Research Organization (CASRO) method and was based on the ratio of completed interviews to the sum of completed interviews, refusals, and a standard fraction of numbers that were working but were either ring/no answer or busy after multiple attempts.34 The CASRO response rate was 61%.
Analyses Data on PA behavior were cleaned and edited following standard quality control procedures.23 This included imputation for a small percentage of values, particularly when reported duration of activity was clearly out of range (e.g., reporting 8 hours per day of moderate and/or vigorous activity was imputed to 15 minutes, based on the BRFSS PA Data Cleaning Module [C Macera, Centers for Disease Control and Prevention, personal communication, 2001]). PA behavior was grouped into one of two categories for the relationships examined in this paper: (1) meets public health recommendations⫽moderate activity (5 times/week ⫻ 30 minutes/time) and/or vigorous activity (3 times/week ⫻ 20 minutes/time); and (2) insufficient activity⫽those who do not meet the recommendation for moderate activity and do not meet the recommendation for vigorous activity. These algorithms have been developed by the CDC for recent population-based surveys. Unadjusted odds ratios (uORs), multivariate-adjusted odds ratios (aORs), and 95% confidence intervals (CIs) were calculated to compare (1) receipt of PA advice and counseling support by respondent demographic and medical condition variables and (2) the level of PA by various sociodemographic and provider advice categories. We assumed that those who did not report receiving advice to exercise also did not receive more intensive counseling or support. In developing logistic regression models based on multiple potential confounders, independent correlates were added to the model if they had been consistently shown to be significant predictors of PA in national studies.1,35 The variables selected in the final modeling included age, gender, race/ ethnicity, household income, and education level. For logistic regression analyses, PA behavior was dichotomized to meeting public health recommendations versus insufficient activity and inactivity. Dichotomization allows careful examination of the current public health recommendation regarding PA level and calculation of epidemiologic measures of association using logistic modeling.
there was an even distribution on number of physician office visits per year and all of the variables in Table 1. Also shown in Table 1, 28% of respondents reported receiving advice to increase their PA level, which was comparable to or slightly less than the percentage that reported physician advice regarding other preventive behaviors. The single exception to this was advice to quit smoking (asked only of current smokers, 21.6% of respondents; all other questions were based on all respondents), which was reported by over 70% of smokers. In general, women, older patients, nonwhites, and patients with a regular doctor, those with four or more visits, and those with multiple chronic illnesses were more likely to have received advice to increase PA (Table 2). Logistic regression analyses did not reveal significant associations between PA advice and education, income, marital status, or type of insurance. Similar associations were found for advice to engage in other preventive health behaviors, with the exception of advice to quit smoking, which showed few associations. Unfortunately, fewer than half of those who reported having received advice to increase their PA levels reported also receiving either help developing an exercise plan or follow-up support— counseling components generally considered necessary to produce and maintain behavior change (Table 3). Specifically, only about 40% of respondents who received advice also reported receiving help in making a specific exercise plan or follow-up support. As can be seen, respondents who were more likely to receive help and follow-up tended to be older and nonwhite, to have a regular doctor (for follow-up support only), to have more chronic illnesses, and to make more visits to the doctor. Among the 28% of respondents who did receive advice to increase exercise, the 40% who received follow-up support were more likely to meet PA recommendations than those who did not (aOR⫽1.83, 95% CI⫽1.24 –2.69). The 40% who reported being helped to develop a specific PA plan were somewhat more likely to meet recommendations (aOR⫽1.25, 95% CI⫽0.84 –1.86), but this relationship was not significant.
Discussion Results Approximately two thirds of the respondents were female, and the survey was successful in gathering data from adults representing a large range of ages, over 25% of whom were African American (Table 1). About three quarters had a regular doctor and many were from lower-income households. Three quarters of respondents reported household annual incomes ⬍$50,000, with almost 40% having incomes ⬍$20,000. More than half had one or more chronic illnesses, and 192
Only 28% of a random sample of adults reported receiving advice from their physicians to engage in regular exercise. An even smaller proportion, 11% (or approximately 40% of those who received advice), reported assistance from their physicians in planning an exercise routine or follow-up support regarding their exercise patterns. Taken together, these findings replicate others,36 indicating substantial lack of attention to PA in spite of growing evidence for its importance. These rates of advice and counseling appear roughly comparable to those reported for other health
American Journal of Preventive Medicine, Volume 21, Number 3
Table 2. Adjusted odds ratio (95% CI) for physician’s advice among participants in U.S. Physical Activity Study, 1999 –2000a Characteristic Gender Female Male Age 18–29 30–44 45–64 65⫹ Race/ethnicity White Black/African-American Other Education ⬍High School (HS) HS graduate or some post HS College grad Post grad or professional degree Income, $ ⬍10K 10K–⬍20K 20K–⬍50K ⱖ50K Doctor for regular health care Yes No # of doctor visits per year 0–1 2–3 4⫹ Type of insurance HMO PPO or point of service Traditional None Marital status Married or member of unmarried couple Divorced, widowed, separated, never married # of chronic illnesses 0 1–2 3⫹
More exercise
Eat more fruits and vegetables
Reduce fat (diet) Reduce stress
Quit smoking
1.79 (1.39–2.29) 1.56 (1.23–1.98) 1.30 (1.02–1.66) 1.00 1.00 1.00
1.66 (1.31–2.10) 1.00
1.33 (0.80–2.20) 1.00
1.00 1.28 (0.94–1.75) 2.08 (1.52–2.84) 1.73 (1.19–2.51)
1.00 1.71 (1.25–2.36) 2.86 (2.07–3.95) 3.05 (2.09–4.45)
1.00 1.21 (0.91–1.61) 1.19 (0.88–1.60) 0.83 (0.58–1.21)
1.00 1.70 (0.93–3.13) 1.53 (0.81–2.91) 6.07 (1.30–28.28)
1.00 1.00 1.00 1.67 (1.29–2.17) 2.59 (2.01–3.33) 2.04 (1.57–2.64) 1.69 (1.23–2.32) 2.29 (1.68–3.12) 1.92 (1.39–2.65)
1.00 1.25 (0.97–1.61) 1.46 (1.08–1.97)
1.00 1.14 (0.62–2.11) 0.79 (0.40–1.57)
1.28 (0.75–2.20) 1.21 (0.75–1.96) 1.14 (0.67–1.92) 1.00
1.72 (0.99–2.99) 1.43 (0.87–2.35) 1.34 (0.78–2.31) 1.00
1.37 (0.81–2.32) 1.23 (0.77–1.97) 1.36 (0.82–2.26) 1.00
2.72 (0.74–10.00) 3.19 (0.96–10.53) 3.31 (0.84–13.04) 1.00
1.03 (0.69–1.53) 1.37 (0.92–2.04) 1.01 (0.67–1.53) 0.80 (0.55–1.17) 1.28 (0.88–1.88) 1.04 (0.71–1.53) 0.98 (0.70–1.37) 1.11 (0.79–1.58) 1.26 (0.89–1.77) 1.00 1.00 1.00
1.20 (0.81–1.76) 1.21 (0.84–1.73) 1.11 (0.80–1.54) 1.00
1.28 (0.50–3.23) 1.22 (0.50–2.95) 0.73 (0.34–1.58) 1.00
1.76 (1.31–2.38) 2.01 (1.50–2.70) 1.95 (1.44–2.65) 1.00 1.00 1.00
1.95 (1.46–2.59) 1.00
3.75 (2.18–6.44) 1.00
1.00 1.00 1.00 1.02 (0.74–1.42) 1.00 (0.72–1.38) 1.44 (1.03–2.02) 1.82 (1.31–2.52) 1.47 (1.06–2.03) 2.08 (1.48–2.91)
1.00 1.53 (1.10–2.12) 2.71 (1.95–3.77)
1.00 1.16 (0.54–2.52) 3.11 (1.30–7.47)
1.11 (0.77–1.58) 1.31 (0.93–1.85) 1.16 (0.83–1.62) 1.00
0.91 (0.64–1.31) 1.40 (0.99–1.98) 1.33 (0.95–1.87) 1.00
1.53 (1.09–2.16) 1.44 (1.03–2.03) 1.72 (1.24–2.38) 1.00
2.78 (1.32–5.85) 2.16 (1.03–4.54) 1.91 (0.98–3.75) 1.00
1.13 (0.89–1.44) 1.12 (0.89–1.42) 1.03 (0.81–1.31)
0.91 (0.73–1.15)
0.98 (0.58–1.66)
1.00
1.00
1.00
1.00 0.92 (0.69–1.24) 1.32 (0.98–1.79) 1.58 (1.10–2.25)
1.85 (1.06–3.23) 1.45 (0.87–2.39) 1.14 (0.65–1.98) 1.00
1.36 (0.96–1.92) 1.33 (0.95–1.88) 1.35 (0.97–1.87) 1.00
1.00
1.00
1.00 1.00 1.00 1.00 1.00 2.63 (2.00–3.46) 2.06 (1.58–2.69) 2.58 (1.95–3.41) 2.78 (2.13–3.63) 3.46 (1.93–6.22) 6.02 (4.11–8.80) 4.84 (3.32–7.04) 8.26 (5.62–12.13) 7.28 (4.95–10.71) 6.20 (2.30–16.70)
a When appropriate, adjusted for age, gender, income, race, and education. CI, confidence interval.
behaviors, except for smoking cessation advice, which was higher. Although implemented far less than it should be, advice to patients concerning exercise does not seem to be randomly distributed. It was more commonly reported among those who had more frequent visits to the doctor. This may be because more frequent visits create more opportunities during which exercise can be addressed. But, taken together with the finding (controlling for other factors) that older adults are more likely to report physicians’ advice to exercise, it suggests that advice to exercise is cued by patient health conditions that physicians may judge as benefiting from
exercise. Previous research37 has also shown advice to exercise more commonly reported by those with obvious health conditions. Such conditions might include clinical conditions, such as arthritis, that both increase with age and benefit from appropriate exercise. Sedentary lifestyle may also be a cue for advice. In this regard, the offering of advice regarding exercise mirrors data concerning other risk behaviors. For example, both patient and physician reports indicate that physicians’ advice to quit smoking is more likely for patients with smoking-related disease.38 It was also encouraging that nonwhites and women in the present survey were more likely to report advice to exercise. Am J Prev Med 2001;21(3)
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Table 3. Percentages and adjusted odds ratios (95% CI) for reporting specific type of physician support among participants in U.S. Physical Activity Study, 1999 –2000 (N⫽1818)a Helped plan exercise program Characteristic Gender Female Male Age group 18–29 30–44 45–64 65⫹ Race/ethnicity White Black/African-American Other Education ⬍High school (HS) graduate HS grad or some post HS College grad Post grad or professional degree Income, $ ⬍10K 10K–⬍20K 20K–⬍50K ⱖ50K Health care Yes No # of doctor visits per year 0–1 2–3 4⫹ Type of insurance Yes, HMO Yes, PPO or point of service Yes, traditional None Marital status Married or member of unmarried couple Divorced, widowed, separated, or never married # of chronic illnesses 0 1–2 3⫹
Received both help with plan and follow-up
Followed up with program
%
aOR (95% CI)
%
aOR (95% CI)
%
aOR (95% CI)
11.6 9.2
1.24 (0.87–1.77) 1.00
13.1 9.5
1.49 (1.05–2.11) 1.00
8.5 6.9
1.21 (0.81–1.81) 1.00
6.0 10.2 15.0 12.6
1.00 1.92 (1.18–3.12) 2.95 (1.82–4.78) 2.66 (1.51–4.67)
8.0 10.8 15.4 14.6
1.00 1.63 (1.03–2.59) 2.44 (1.54–3.85) 2.80 (1.66–4.71)
4.5 7.8 10.0 10.2
1.00 1.90 (1.10–3.29) 2.38 (1.37–4.15) 2.95 (1.59–5.47)
6.7 16.8 12.9
1.00 3.01 (2.06–4.38) 2.73 (1.72–4.32)
9.3 16.7 12.2
1.00 2.16 (1.52–3.07) 1.74 (1.10–2.73)
5.1 12.6 8.8
1.00 2.72 (1.79–4.14) 2.23 (1.31–3.80)
14.2 10.9 7.3 9.3
1.07 (0.49–2.58) 1.08 (0.53–2.22) 0.87 (0.39–1.95) 1.00
14.5 11.6 11.3 9.3
1.18 (0.55–2.52) 1.20 (0.61–2.38) 1.31 (0.63–2.75) 1.00
10.9 7.7 6.3 6.8
1.02 (0.42–2.46) 0.96 (0.45–2.20) 1.02 (0.43–2.43) 1.00
15.0 10.1 11.3 7.4
1.41 (0.76–2.58) 1.07 (0.59–1.96) 1.40 (0.82–2.39) 1.00
16.4 9.8 11.5 11.7
1.04 (0.61–1.78) 0.67 (0.39–1.15) 0.92 (0.58–1.46) 1.00
11.8 7.7 7.5 6.7
1.24 (0.64–2.38) 0.92 (0.48–1.76) 1.04 (0.58–1.85) 1.00
12.4 5.5
2.13 (1.32–3.45) 1.00
14.2 4.5
3.12 (1.84–5.28) 1.00
9.5 2.9
3.42 (1.80–6.52) 1.00
7.7 9.0 18.8
1.00 1.02 (0.62–1.69) 1.93 (1.20–3.09)
6.6 12.4 20.5
1.00 1.71 (1.04–2.83) 2.83 (1.73–4.61)
4.3 7.0 15.2
1.00 1.44 (0.78–2.67) 2.92 (1.63–5.21)
10.9 11.9 10.8 10.0
1.07 (0.64–1.79) 1.58 (0.96–2.57) 1.09 (0.67–1.79) 1.00
12.1 14.0 12.3 8.9
1.37 (0.82–2.30) 1.84 (1.13–3.02) 1.36 (0.83–2.23) 1.00
8.1 9.3 7.8 6.7
1.23 (0.67–2.25) 1.87 (1.06–3.31) 1.27 (0.71–2.27) 1.00
10.6 11.0
1.15 (0.82–1.62) 1.00
11.3 12.6
1.02 (0.74–1.42) 1.00
6.9 9.0
0.90 (0.61–1.33) 1.00
5.1 11.5 25.3
1.00 2.49 (1.63–3.83) 5.98 (3.54–10.11)
5.4 12.8 28.4
1.00 2.63 (1.73–3.98) 7.81 (4.71–12.95)
3.6 8.2 20.1
1.00 2.72 (1.65–4.49) 7.94 (4.36–14.45)
a When appropriate, adjusted for age, gender, income, race, and education. aOR, adjusted odds ratio; CI, confidence interval.
Similarly, assistance in planning an exercise routine and follow-up of PA levels appear to be directed toward those whom physicians may well perceive as being more in need of exercise. The offering of assistance in planning an exercise regimen and follow-up regarding patients’ PA are both more common among those who report more chronic diseases, are older, are nonwhite, are female (for follow-up support only), or report more visits to the doctor. We explored relationships among assistance and follow-up support among those patients who had re194
ceived advice. Within this group, those reporting follow-up support were more likely to report PA, the OR for follow-up support (adjusted for age, gender, race, income, and education) was 1.83 (p⬍0.05). The results for assistance in developing an exercise plan were in the same direction, but not significant. Although limited by being cross-sectional and post-hoc, these analyses suggest that follow-up support may be important for successful behavior change. These findings and other reviews39 – 41 indicate the utility of self-management counseling and follow-up
American Journal of Preventive Medicine, Volume 21, Number 3
support in maintaining behavior change, but also the infrequency of their provision. Ongoing follow-up may be especially important in PA. For example, most individuals who quit smoking reach some point when their likelihood of relapse is low and, presumably, the effort of remaining abstinent is also low. In contrast, PA continues to require time, attention, and energy for as long as it is maintained. Ongoing support and encouragement by health professionals is likely to be helpful in maintaining it, especially as individuals age and injuries or comorbid conditions create increasing barriers to PA. Physician training programs for PA counseling need to go beyond asking a single question to include effective behavior change and maintenance strategies. Earlier studies found lower-income individuals and those with less education or on Medicaid to be less likely to receive physician advice to exercise,36,37 whereas our study did not replicate these relationships. The present finding of more frequent advice, assistance in planning, and follow-up support for minority members is, to our knowledge, unique in the literature. This bears replication in other representative studies and is encouraging regarding attempts to reduce the disparities in health and health care.1 Limitations of the current project are that it is based on self-report data and cross-sectional in design. It would have been helpful to have recorded information on the time elapsed since the last medical office visit to investigate potential recall bias issues. Prospective studies of health professionals’ advice to exercise and related interventions to promote PA are needed. These studies should include objective measures of both patient–provider interactions to promote PA (e.g., tape recordings) and of activity itself (e.g., activity monitors). In summary, the frequency with which physicians provide advice to exercise and follow-up support fails to reflect growing evidence of the importance of PA in prevention and disease management. To the extent that it is provided, advice is likely directed to those with clinical circumstances indicating a need for exercise or the possibility of benefit from it. Unfortunately, this pattern of advice overlooks the preventive role of PA.20 PA needs to join weight, blood pressure, and, more recently, smoking,42 as a vital sign conducted during routine visits. As with other behavior and education components of health care, just educating individual clinicians on recommended practice patterns is unlikely to be successful. Rather, progress will most likely follow system changes and practice redesign to encourage improved practice.43,44 In particular, ongoing attention and follow-up from health professionals may be especially helpful for PA, the benefits of which are substantial but also require maintenance for the duration of individuals’ lives.45
This study was funded through the Centers for Disease Control and Prevention, contract U48/CCU710806 (Prevention Research Centers Program), including support from the Community Prevention Study of the National Institutes of Health’s Women’s Health Initiative. Human subjects approval was obtained from the Saint Louis University Institutional Review Board. We are grateful for the assistance of Patsy Henderson, Nancy Noedel, and Mary Cregger of Battelle for assistance in data collection; Frank Markowitz of GENESYS Sampling Systems for sampling help; and Tracey Cannon and Katie Dugan of the Prevention Research Center at Saint Louis University and Barbara McCray at AMC Cancer Research Center for administrative support.
References 1. U.S. Department of Health and Human Services. Physical activity and health. A report of the Surgeon General Executive Summary. Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, The President’s Council on Physical Fitness and Sports. Atlanta, GA: U.S. Government Printing Office, 1996. 2. National Institutes of Health. Physical activity and cardiovascular health. JAMA 1996;276:241– 6. 3. Harris SS, Caspersen CJ, DeFriese GH, et al. Physical activity counseling for healthy adults as a primary preventive intervention in the clinical setting: report for the U.S. Preventive Services Task Force. JAMA 1989;261:3590 – 8. 4. Pate RR, Pratt M, Blair SN, et al. Physical activity and public health: a recommendation from the Centers for Disease Control and Prevention and the American College of Sports Medicine. JAMA 1995;273:402–7. 5. Ainsworth BE, Macera CA. Physical inactivity. In: Brownson RC, Remington PL, Davis JR, eds. Chronic disease epidemiology and control. Washington, DC: American Public Health Association, 1998:191–213. 6. Clark NM, Becker MH, Lorig K, Rakowski W, Anderson L. Self-management of chronic disease by older adults: a review and questions for research. J Aging Health 1991;3:3–27. 7. McGinnis JM, Foege WH. Actual causes of death in the United States. JAMA 1993;270:2207–12. 8. Crespo CJ, Ainsworth BE, Keteyian SJ, Heath GW, Smit E. Prevalence of physical inactivity and its relation to social class in U.S. adults: results from the Third National Health and Nutrition Examination Survey. Med Sci Sports Exerc 1999;31:1821–7. 9. Taylor WC, Baranowski T, Young DR. Physical activity interventions in low-income, ethnic minority, and populations with disability. Am J Prev Med 1998;15:334 – 43. 10. Clark DO. Physical activity and its correlates among urban primary care patients aged 55 years or older. J Gerontol 1999;54B:S41– 48. 11. Sallis JF, Owen N. Physical activity and behavioral medicine. Thousand Oaks, CA: Sage Publications, 1999. 12. Stewart AL, Sepsis PG, King AC, McLelland BY, Roitz K, Ritter PL. Evaluation of CHAMPS, a physical activity promotion program for older adults. Ann Behav Med 1997;19:353– 61. 13. Centers for Disease Control and Prevention, National Center for Health Statistics. Current estimates from the National Health Interview Survey. Series 10, No. 200. Hyattsville, MD: U.S. Department of Health and Human Services, 1996. 14. Eakin EG, Glasgow RE, Riley KM. Review of primary care-based physical activity intervention studies: effectiveness and implications for practice and future research. J Fam Pract 2000;49:158 – 68. 15. Simons-Morton DG, Calfas KJ, Oldenburg B, Burton NW. Effects of interventions in health care settings on physical activity or cardiorespiratory fitness. Am J Prev Med 1998;15:413–30. 16. U.S. Department of Health and Human Services. Healthy People 2010: understanding and improving health and objectives for improving health, 2nd ed. 2 vols. Washington, DC: U.S. Government Printing Office, 2000. 17. U.S. Preventive Services Task Force. Guide to clinical preventive services: report of U.S. Preventive Services Task Force, 2nd ed. Washington, DC: Office of Disease Prevention and Health Promotion, U.S. Government Printing Office, 1996. 18. Damush TM, Stewart AL, Millls K, King AC, Ritter PL. Prevalence and correlates of physician recommendations to older adults to exercise. Ann Behav Med 1998;20(supp):S194.
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19. Eakin EG, Glasgow RE. Recruitment of managed care Medicare patients for a physical activity study. Am J Health Promo 1997;12:98 –101. 20. Wee CC, McCarthy EP, Davis RB, Phillips RS. Physician counseling about exercise. JAMA 1999;282:1583– 8. 21. Nawaz H, Adams ML, Katz DL. Physician-patient interactions regarding diet, exercise, and smoking. Prev Med 2000;31:652–7. 22. Gentry EM, Kalsbeek WD, Hogeline GC, et al. The behavioral risk factor surveys: II. Design, methods and estimates from combined state data. Am J Prev Med 1985;1:9 –14. 23. Remington PL, Smith MY, Williamson DF, Anda RF, Gentry EM, Hogelin GC. Design, characteristics, and usefulness of state-based behavioral risk factor surveillance: 1981–1987. Public Health Rep 1988;103:366 –75. 24. Siegel P, Brackbill R, Frazier E, et al. Behavioral risk factor surveillance, 1986 –1990. MMWR Morb Mort Wkly Rep 1991;40:1–23. 25. Brownson RC, Baker EA, Houseman RA, Brennan LK, Bacak SJ. Environmental and policy determinants of physical activity in the United States. Am J Public Health 2001. In press. 26. Brownson RC, Eyler AA, King AC, Shyu Y-L, Brown DR, Homan SR. Reliability of information on physical activity and other chronic disease risk factors among U.S. women aged 40 years or older. Am J Epidemiol 1999;149:379 –91. 27. Brownson RC, Mayer JP, Desseault PG, et al. Developing and evaluating a cardiovascular risk reduction project. Am J Health Behavior 1997;21:333– 44. 28. Hovell MF, Hofstetter CR, Sallis JF, Raug MJD, Barrington E. Correlates of change in walking for exercise: an exploratory analysis. Res Q Exerc Sport 1992;63:425–34. 29. Sallis JF, Grossman RM, Pinski RB, Patterson TL, Nader PR. The development of scales to measure social support for diet and exercise behaviors. Prev Med 1987;16:825–36. 30. Sallis JF, Hovell MF, Hofstetter CR, et al. Distances between homes and exercise facilities related to frequency of exercise among San Diego residents. Public Health Rep 1990;105:179 – 85. 31. Brownson RC, Housemann RA, Brown DR, et al. Promoting physical activity in rural communities: walking trail access, use, and effects. Am J Prev Med 2000;18:235– 41. 32. Manley M, Epps R, Husten C, Glynn T, Shopland D. Clinical interventions in tobacco control: a National Cancer Institute training program for physicians. JAMA 1991;266:3172–3.
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33. Ainsworth BA, Bassett DRJ, Strath SJ, et al. Comparison of three methods of measuring time spent in physical activity. Med Sci Sports Exerc 2000; 32(suppl):S457– 64. 34. American Association for Public Opinion Research. Standard definitions. Final dispositions of case codes and outcome rates for RDD telephone surveys and in-person household surveys. Ann Arbor, MI: American Association for Public Opinion Research, 1998. 35. Brownson RC, Eyler AA, King AC, Brown DR, Shyu Y-L, Sallis JF. Patterns and correlates of physical activity among women aged 40 years and older, United States. Am J Pub Health 2000;90:264 –70. 36. Friedman C, Brownson RC, Peterson DE, Wilkerson JC. Physician advice to reduce chronic disease risk factors. Am J Prev Med 1994;10:367–71. 37. Kreuter MW, Scharff DP, Brennan LK, Lukwago SN. Physician advice for diet and physical activity. Prev Med 1997;26:825–33. 38. Fisher EB Jr, Lichtenstein E, Haire-Joshu D, Morgan GD, Rehberg HR. Methods, successes, and failures of smoking cessation programs. Annu Rev Med 1993;44:481–513. 39. Kottke TE, Battista RN, DeFriese GH. Attributes of successful smoking cessation interventions in medical practice: a meta-analysis of 39 controlled trials. JAMA 1988;259:2882–9. 40. Fiore MC, Bailey WC, Cohen SJ, et al. Treating tobacco use and dependence: clinical practice guideline. Rockville, MD: Public Health Service, U.S. Department of Health and Human Services, 2000. 41. Glasgow RE, Fisher EB, Anderson BJ, et al. Behavioral science in diabetes: contributions and opportunities. Diabetes Care 1999;22:832– 43. 42. Fiore M, Jorenby D, Schensky A, Smith S, Bauer R, Baker T. Smoking status as the new vital sign: effect on assessment and intervention in patients who smoke. Mayo Clin Proc 1995;70:209 –13. 43. Wagner EH, Glasgow RE, Davis C, et al. Quality improvement in chronic illness care: a collaborative approach. Jt Comm J Qual Improv 2001;27:63– 80. 44. Glasgow RE, Hiss RG, Anderson RM, et al. Report of Health Care Delivery Work Group: behavioral research related to the establishment of a chronic disease model for diabetes care. Diabetes Care 2001;24:124 –30. 45. Orleans CT. Promoting the maintenance of health behavior change: recommendations for the next generation of research and practice. Health Psychol 2000;19:76 – 83.
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A diverse sample of U.S. adults (N⫽1818), with oversampling of lower-income households, was surveyed about their PA level as well as a host of social, environmental, and physician counseling issues.
Results:
Overall, 28% of respondents reported receiving physician advice to increase their PA level. Of those who received advice, only 38% received help formulating a specific activity plan and 42% received follow-up support. Patients who received advice and support were more likely to be older, nonwhite, and to have more chronic illnesses and more contact with their doctor.
Conclusions: Physician advice, counseling, and follow-up are important components of the socialenvironmental supports needed to increase population PA levels. Health system changes, including teaching communication skills, prompts to use those skills, and system changes to support attention to PA, are needed to extend promotion of PA to more patients. Medical Subject Headings (MeSH): counseling; exercise, health promotion; physician– patient relations (Am J Prev Med 2001;21(3):189 –196) © 2001 American Journal of Preventive Medicine
R
egular physical activity (PA) is essential for disease prevention and health promotion.1– 4 Regular PA reduces the risk of diabetes, colon cancer, hypertension, and obesity.1 Physical inactivity is an independent heart disease risk factor of similar magnitude (relative risk of 1.9) to smoking, hypertension, and hypercholesterolemia.5 PA promotes psychological well-being, and builds and maintains healthy bones, muscles, and joints, thus reducing the risk of falls in the elderly and increasing functional independence.1 PA is also an important part of the self-care regimen for many chronic illnesses.6 In 1990, approximately 300,000 deaths were attributed to physical inactivity and poor nutrition, while 400,000 deaths were
From the AMC Cancer Research Center, Center for Behavioral and Community Studies (Glasgow, Eakin), Denver, Colorado; Queensland University of Technology (Eakin), Kelvin Grove, Queensland, Australia; Division of Health Behavior Research and Department of Psychology (Fisher), Washington University, St. Louis, Missouri; and Department of Community Health and Prevention Research Center, School of Public Health, St. Louis University (Bacak, Brownson), St. Louis, Missouri Address correspondence and reprint requests to: Russell E. Glasgow, PhD, AMC Cancer Research Center, Center for Behavioral and Community Studies, 1600 Pierce Street, Denver, CO 80214. E-mail: [email protected].
attributed to tobacco.5,7 Sedentary behavior has been estimated to cost the United States $5.7 billion annually.7 National recommendations on PA from the American College of Sports Medicine (ACSM) and the Centers for Disease Control and Prevention (CDC) state that all adults should accumulate 30 minutes a day of moderate-intensity activity on five or more days of the week. However, national survey data indicate that approximately 68% of U.S. adults do not achieve this recommended level.5 Among special populations, such as the poor and underserved, older adults, and those with chronic illness, there is even greater need for attention to PA.1,8,9 A recent study of 771 older adult patients from an urban primary healthcare center serving low-income patients revealed that only 10% met the ACSM/CDC guidelines for regular moderate PA.10 In addition to facing the common barriers to PA (e.g., lack of time, lack of support, and lack of interest), members of these special populations face additional challenges, making the initiation and maintenance of PA even more difficult. These challenges include unsafe or unappealing environmental conditions, lack of community or neighborhood resources, and lack of money or transportation. Additional barriers faced by
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those with chronic illness, which are disproportionately prevalent among minority and low-income populations, include pain and discomfort as well as psychological barriers, such as depression, and beliefs that those with chronic illness should not exercise.10 –12 A visit to a primary healthcare provider appears to be an opportune time for PA counseling, especially due to the fact that the majority of adults see their healthcare providers three or more times a year.13 Numerous studies have evaluated the outcomes of primary care– based PA interventions.14,15 The national health promotion and disease prevention objectives in Healthy People 201016 and by the U.S. Preventive Services Task Force17 recommend that physicians and other healthcare providers counsel their patients to be physically active as part of routine healthcare visits, yet the majority of physicians do not do so. Previous studies of older adults found that between 22% to 48% reported having received advice regarding PA from their physician.18,19 Finally, recent studies based on patients who reported recent medical checkups suggest that 34% of patients received physician advice to exercise20 and 56% of patients were questioned about exercise.21 Both studies20,21 indicated that patients with higher income levels were more likely to have PA discussed. The main purposes of this paper are threefold: (1) to report on patient recall of interactions with primary care physicians regarding PA and other preventive behaviors; (2) to study a large and more representative sample than most previous research, including a sizable proportion of low-income and minority respondents, to allow investigation of the relationship of these factors to PA counseling; and (3) to examine relationships between more intensive components of PA counseling (e.g., activity planning and follow-up) and patient characteristics. Information related to purposes 2 and 3 has not been reported previously and was obtained from a national survey that included an oversampling of lowerincome individuals.
Methods Sampling Data were collected via telephone survey, using a modified version of the sampling plan of the Behavioral Risk Factor Surveillance System (BRFSS). The primary objective of the overall survey was to obtain representative data among varied populations across the United States on patterns and determinants of PA. There were no financial or other incentives to respondents, and the survey methods have been described in detail elsewhere.22–24 The cross-sectional risk factor survey used a random-digit-dialing technique to collect data.25 To obtain a representative sample of lower-income individuals, ZIP codes were oversampled that had ⱖ32% of residents below the federal poverty level. Once the ZIP codes were selected, the area code/exchange combinations that were at least 70% within the ZIP code defined area were determined and used as the final sample frame for this stratum. The
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random-digit-dialing sample that was used for this project can be best characterized as a single-stage epsem (equal probability selection method) sample of all residential telephone numbers (listed, unlisted, and unpublished numbers) in the defined sample frame. The system used a database consisting of all residential telephone exchanges, working phone bank information, and various geographic variables, such as state, county, and zip code. On a national basis, this definition covers an estimated 96.4% of all residential telephone numbers and 99.96% of listed residential numbers. The sample frame consisted of the set of all area code/exchange combinations and their associated working banks, which met the criteria listed above. The result was that every potential telephone number within the defined sample frame had a known and equal probability of selection. During interviews, if contact could not be made after three attempts, another number was selected from the primary sampling unit.
Instrumentation and Data Collection The survey instrument was developed using a combination of questions from the BRFSS, the National Health Interview Survey, and other recent surveys.22,23,26 –31 When valid and reliable scales were documented in the literature and available, every effort was made to use these with the scale intact. In a few cases, adaptations were made from in-person to telephone administration (e.g., asking a “yes/no” question rather than a checklist that would be used in an in-person interview). The final instrument contained a total of 90 questions, including skip patterns, with an average administration time of 30 minutes. An initial set of questions asked about an individual’s access to health care (e.g., “Do you have any kind of healthcare coverage, including health insurance, prepaid plans such as HMOs, or government plans such as Medicare, Medicaid, or Veteran’s care?”). Additional questions focused on health professional advice for various preventive behaviors (i.e., PA, fruit and vegetable consumption, weight reduction, dietary fat reduction). These questions were included to compare results on PA advice to those in other health promotion areas. For persons who had received PA advice, further questions— modeled on the “4 A’s” counseling approach (Ask, Advise, Assist, and Arrange Follow-up) recommended by the National Cancer Institute32—were asked specifically about developing a plan for exercise and follow-up from a provider on subsequent visits. Specific questions were: (1) “Have you ever been advised within the last year by a doctor or other health professional to exercise more?” (Yes/No); (2) “Has your doctor or healthcare provider helped you to develop a plan to increase your exercise?” (Yes/No); (3) “Has your doctor or healthcare provider followed up with you at subsequent visits to see how you were doing to increase your exercise?” (Yes/No). Newly developed questions on PA behavior focused on moderate and vigorous PA in the domains of occupational PA, time spent in non-occupational walking, moderate-intensity recreational activities, and vigorous-intensity recreational activities. These questions are designed to estimate compliance with new public health recommendations4 and have been previously tested for reliability and validity.33 Between September 1999 and January 2000, interviews were completed for 1818 men and women (Table 1). Experienced
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Table 1. Frequency of physicians’ advice within various sociodemographic and medical characteristic subgroups among participants in U.S. Physical Activity Study, 1999 –2000 (N⫽1818)
Characteristic Gender Female Male Missing Age 18–29 30–44 45–64 65⫹ Missing Race/ethnicity White Black/African-American Other Missing Education ⬍High school (HS) HS graduate or some post HS College grad Post grad or professional degree Missing Income, $c ⬍10K 10K–⬍20K 20K–⬍50K ⱖ50K Missing Doctor for regular health care Yes No Missing # of doctor visits per year 0–1 2–3 4⫹ Missing Type of insurance HMO PPO or point of service Traditional None Missing Marital status Married or member of unmarried couple Divorced, widowed, separated, never married Missing # of chronic illnesses 0 1–2 3⫹ Missing
a
a
More exerciseb
Eat more fruits and vegetablesb
Reduce fatb (diet)
Reduce Quit stressb smokingc
Number
Percentage
1220 598 0
67.1 32.9 0
31.7 21.6
35.9 25.4
30.9 25.1
34.5 24.3
74.3 67.8
487 548 479 295 9
26.8 30.1 26.3 16.2 0.5
22.0 26.1 35.7 31.3
32.0 26.6 33.8 41.5
19.1 25.7 36.7 38.2
30.2 32.8 33.4 25.5
64.8 73.8 73.0 82.8
971 546 295 6
53.4 30.0 16.2 0.4
24.1 34.8 30.8
23.1 46.2 38.6
23.6 37.7 30.5
28.4 34.1 35.3
71.1 76.9 68.5
330 1068 301 118 1
18.2 58.7 16.6 6.5 0.1
33.0 28.5 24.7 24.6
44.5 32.7 23.7 19.5
37.0 28.4 24.7 22.9
33.0 31.0 32.3 23.7
73.0 73.1 70.0 50.0
347 378 610 283 200
19.1 20.8 33.6 15.6 11.0
34.0 25.9 28.1 26.9
43.2 36.0 28.7 22.6
32.6 29.2 30.0 23.7
34.0 32.8 30.6 27.9
77.4 76.2 65.9 71.7
1397 421 0
76.8 23.2 0
31.6 17.6
35.4 22.9
32.4 17.6
34.0 21.7
78.9 53.7
376 542 526 374
20.7 29.8 28.9 20.6
24.5 27.3 40.9
26.9 31.5 44.9
21.3 30.6 41.0
22.1 31.4 44.3
70.4 73.6 84.6
421 473 511 360 53
23.2 26.0 28.1 19.8 2.9
28.5 29.7 29.7 5.0
34.7 30.3 34.1 31.4
27.3 29.9 32.3 26.1
32.8 30.1 34.5 26.9
80.0 73.5 73.8 63.5
884
48.6
29.1
30.2
28.4
30.3
71.0
931
51.2
27.7
34.6
29.5
32.0
72.7
3
0.2
830 686 289 13
45.7 37.7 15.9 0.7
16.7 32.8 50.9
21.9 35.1 56.1
15.3 32.8 58.7
20.4 35.8 50.5
59.5 79.6 85.9
a
Number and percentage in entire population. Percentage of respondents answering “yes” to advice questions. c Percentage, for current cigarette smokers only (n⫽393). b
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interviewers conducted the interviews, and each interviewer underwent at least 16 hours of training. The response rate was calculated according to the Council of American Survey Research Organization (CASRO) method and was based on the ratio of completed interviews to the sum of completed interviews, refusals, and a standard fraction of numbers that were working but were either ring/no answer or busy after multiple attempts.34 The CASRO response rate was 61%.
Analyses Data on PA behavior were cleaned and edited following standard quality control procedures.23 This included imputation for a small percentage of values, particularly when reported duration of activity was clearly out of range (e.g., reporting 8 hours per day of moderate and/or vigorous activity was imputed to 15 minutes, based on the BRFSS PA Data Cleaning Module [C Macera, Centers for Disease Control and Prevention, personal communication, 2001]). PA behavior was grouped into one of two categories for the relationships examined in this paper: (1) meets public health recommendations⫽moderate activity (5 times/week ⫻ 30 minutes/time) and/or vigorous activity (3 times/week ⫻ 20 minutes/time); and (2) insufficient activity⫽those who do not meet the recommendation for moderate activity and do not meet the recommendation for vigorous activity. These algorithms have been developed by the CDC for recent population-based surveys. Unadjusted odds ratios (uORs), multivariate-adjusted odds ratios (aORs), and 95% confidence intervals (CIs) were calculated to compare (1) receipt of PA advice and counseling support by respondent demographic and medical condition variables and (2) the level of PA by various sociodemographic and provider advice categories. We assumed that those who did not report receiving advice to exercise also did not receive more intensive counseling or support. In developing logistic regression models based on multiple potential confounders, independent correlates were added to the model if they had been consistently shown to be significant predictors of PA in national studies.1,35 The variables selected in the final modeling included age, gender, race/ ethnicity, household income, and education level. For logistic regression analyses, PA behavior was dichotomized to meeting public health recommendations versus insufficient activity and inactivity. Dichotomization allows careful examination of the current public health recommendation regarding PA level and calculation of epidemiologic measures of association using logistic modeling.
there was an even distribution on number of physician office visits per year and all of the variables in Table 1. Also shown in Table 1, 28% of respondents reported receiving advice to increase their PA level, which was comparable to or slightly less than the percentage that reported physician advice regarding other preventive behaviors. The single exception to this was advice to quit smoking (asked only of current smokers, 21.6% of respondents; all other questions were based on all respondents), which was reported by over 70% of smokers. In general, women, older patients, nonwhites, and patients with a regular doctor, those with four or more visits, and those with multiple chronic illnesses were more likely to have received advice to increase PA (Table 2). Logistic regression analyses did not reveal significant associations between PA advice and education, income, marital status, or type of insurance. Similar associations were found for advice to engage in other preventive health behaviors, with the exception of advice to quit smoking, which showed few associations. Unfortunately, fewer than half of those who reported having received advice to increase their PA levels reported also receiving either help developing an exercise plan or follow-up support— counseling components generally considered necessary to produce and maintain behavior change (Table 3). Specifically, only about 40% of respondents who received advice also reported receiving help in making a specific exercise plan or follow-up support. As can be seen, respondents who were more likely to receive help and follow-up tended to be older and nonwhite, to have a regular doctor (for follow-up support only), to have more chronic illnesses, and to make more visits to the doctor. Among the 28% of respondents who did receive advice to increase exercise, the 40% who received follow-up support were more likely to meet PA recommendations than those who did not (aOR⫽1.83, 95% CI⫽1.24 –2.69). The 40% who reported being helped to develop a specific PA plan were somewhat more likely to meet recommendations (aOR⫽1.25, 95% CI⫽0.84 –1.86), but this relationship was not significant.
Discussion Results Approximately two thirds of the respondents were female, and the survey was successful in gathering data from adults representing a large range of ages, over 25% of whom were African American (Table 1). About three quarters had a regular doctor and many were from lower-income households. Three quarters of respondents reported household annual incomes ⬍$50,000, with almost 40% having incomes ⬍$20,000. More than half had one or more chronic illnesses, and 192
Only 28% of a random sample of adults reported receiving advice from their physicians to engage in regular exercise. An even smaller proportion, 11% (or approximately 40% of those who received advice), reported assistance from their physicians in planning an exercise routine or follow-up support regarding their exercise patterns. Taken together, these findings replicate others,36 indicating substantial lack of attention to PA in spite of growing evidence for its importance. These rates of advice and counseling appear roughly comparable to those reported for other health
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Table 2. Adjusted odds ratio (95% CI) for physician’s advice among participants in U.S. Physical Activity Study, 1999 –2000a Characteristic Gender Female Male Age 18–29 30–44 45–64 65⫹ Race/ethnicity White Black/African-American Other Education ⬍High School (HS) HS graduate or some post HS College grad Post grad or professional degree Income, $ ⬍10K 10K–⬍20K 20K–⬍50K ⱖ50K Doctor for regular health care Yes No # of doctor visits per year 0–1 2–3 4⫹ Type of insurance HMO PPO or point of service Traditional None Marital status Married or member of unmarried couple Divorced, widowed, separated, never married # of chronic illnesses 0 1–2 3⫹
More exercise
Eat more fruits and vegetables
Reduce fat (diet) Reduce stress
Quit smoking
1.79 (1.39–2.29) 1.56 (1.23–1.98) 1.30 (1.02–1.66) 1.00 1.00 1.00
1.66 (1.31–2.10) 1.00
1.33 (0.80–2.20) 1.00
1.00 1.28 (0.94–1.75) 2.08 (1.52–2.84) 1.73 (1.19–2.51)
1.00 1.71 (1.25–2.36) 2.86 (2.07–3.95) 3.05 (2.09–4.45)
1.00 1.21 (0.91–1.61) 1.19 (0.88–1.60) 0.83 (0.58–1.21)
1.00 1.70 (0.93–3.13) 1.53 (0.81–2.91) 6.07 (1.30–28.28)
1.00 1.00 1.00 1.67 (1.29–2.17) 2.59 (2.01–3.33) 2.04 (1.57–2.64) 1.69 (1.23–2.32) 2.29 (1.68–3.12) 1.92 (1.39–2.65)
1.00 1.25 (0.97–1.61) 1.46 (1.08–1.97)
1.00 1.14 (0.62–2.11) 0.79 (0.40–1.57)
1.28 (0.75–2.20) 1.21 (0.75–1.96) 1.14 (0.67–1.92) 1.00
1.72 (0.99–2.99) 1.43 (0.87–2.35) 1.34 (0.78–2.31) 1.00
1.37 (0.81–2.32) 1.23 (0.77–1.97) 1.36 (0.82–2.26) 1.00
2.72 (0.74–10.00) 3.19 (0.96–10.53) 3.31 (0.84–13.04) 1.00
1.03 (0.69–1.53) 1.37 (0.92–2.04) 1.01 (0.67–1.53) 0.80 (0.55–1.17) 1.28 (0.88–1.88) 1.04 (0.71–1.53) 0.98 (0.70–1.37) 1.11 (0.79–1.58) 1.26 (0.89–1.77) 1.00 1.00 1.00
1.20 (0.81–1.76) 1.21 (0.84–1.73) 1.11 (0.80–1.54) 1.00
1.28 (0.50–3.23) 1.22 (0.50–2.95) 0.73 (0.34–1.58) 1.00
1.76 (1.31–2.38) 2.01 (1.50–2.70) 1.95 (1.44–2.65) 1.00 1.00 1.00
1.95 (1.46–2.59) 1.00
3.75 (2.18–6.44) 1.00
1.00 1.00 1.00 1.02 (0.74–1.42) 1.00 (0.72–1.38) 1.44 (1.03–2.02) 1.82 (1.31–2.52) 1.47 (1.06–2.03) 2.08 (1.48–2.91)
1.00 1.53 (1.10–2.12) 2.71 (1.95–3.77)
1.00 1.16 (0.54–2.52) 3.11 (1.30–7.47)
1.11 (0.77–1.58) 1.31 (0.93–1.85) 1.16 (0.83–1.62) 1.00
0.91 (0.64–1.31) 1.40 (0.99–1.98) 1.33 (0.95–1.87) 1.00
1.53 (1.09–2.16) 1.44 (1.03–2.03) 1.72 (1.24–2.38) 1.00
2.78 (1.32–5.85) 2.16 (1.03–4.54) 1.91 (0.98–3.75) 1.00
1.13 (0.89–1.44) 1.12 (0.89–1.42) 1.03 (0.81–1.31)
0.91 (0.73–1.15)
0.98 (0.58–1.66)
1.00
1.00
1.00
1.00 0.92 (0.69–1.24) 1.32 (0.98–1.79) 1.58 (1.10–2.25)
1.85 (1.06–3.23) 1.45 (0.87–2.39) 1.14 (0.65–1.98) 1.00
1.36 (0.96–1.92) 1.33 (0.95–1.88) 1.35 (0.97–1.87) 1.00
1.00
1.00
1.00 1.00 1.00 1.00 1.00 2.63 (2.00–3.46) 2.06 (1.58–2.69) 2.58 (1.95–3.41) 2.78 (2.13–3.63) 3.46 (1.93–6.22) 6.02 (4.11–8.80) 4.84 (3.32–7.04) 8.26 (5.62–12.13) 7.28 (4.95–10.71) 6.20 (2.30–16.70)
a When appropriate, adjusted for age, gender, income, race, and education. CI, confidence interval.
behaviors, except for smoking cessation advice, which was higher. Although implemented far less than it should be, advice to patients concerning exercise does not seem to be randomly distributed. It was more commonly reported among those who had more frequent visits to the doctor. This may be because more frequent visits create more opportunities during which exercise can be addressed. But, taken together with the finding (controlling for other factors) that older adults are more likely to report physicians’ advice to exercise, it suggests that advice to exercise is cued by patient health conditions that physicians may judge as benefiting from
exercise. Previous research37 has also shown advice to exercise more commonly reported by those with obvious health conditions. Such conditions might include clinical conditions, such as arthritis, that both increase with age and benefit from appropriate exercise. Sedentary lifestyle may also be a cue for advice. In this regard, the offering of advice regarding exercise mirrors data concerning other risk behaviors. For example, both patient and physician reports indicate that physicians’ advice to quit smoking is more likely for patients with smoking-related disease.38 It was also encouraging that nonwhites and women in the present survey were more likely to report advice to exercise. Am J Prev Med 2001;21(3)
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Table 3. Percentages and adjusted odds ratios (95% CI) for reporting specific type of physician support among participants in U.S. Physical Activity Study, 1999 –2000 (N⫽1818)a Helped plan exercise program Characteristic Gender Female Male Age group 18–29 30–44 45–64 65⫹ Race/ethnicity White Black/African-American Other Education ⬍High school (HS) graduate HS grad or some post HS College grad Post grad or professional degree Income, $ ⬍10K 10K–⬍20K 20K–⬍50K ⱖ50K Health care Yes No # of doctor visits per year 0–1 2–3 4⫹ Type of insurance Yes, HMO Yes, PPO or point of service Yes, traditional None Marital status Married or member of unmarried couple Divorced, widowed, separated, or never married # of chronic illnesses 0 1–2 3⫹
Received both help with plan and follow-up
Followed up with program
%
aOR (95% CI)
%
aOR (95% CI)
%
aOR (95% CI)
11.6 9.2
1.24 (0.87–1.77) 1.00
13.1 9.5
1.49 (1.05–2.11) 1.00
8.5 6.9
1.21 (0.81–1.81) 1.00
6.0 10.2 15.0 12.6
1.00 1.92 (1.18–3.12) 2.95 (1.82–4.78) 2.66 (1.51–4.67)
8.0 10.8 15.4 14.6
1.00 1.63 (1.03–2.59) 2.44 (1.54–3.85) 2.80 (1.66–4.71)
4.5 7.8 10.0 10.2
1.00 1.90 (1.10–3.29) 2.38 (1.37–4.15) 2.95 (1.59–5.47)
6.7 16.8 12.9
1.00 3.01 (2.06–4.38) 2.73 (1.72–4.32)
9.3 16.7 12.2
1.00 2.16 (1.52–3.07) 1.74 (1.10–2.73)
5.1 12.6 8.8
1.00 2.72 (1.79–4.14) 2.23 (1.31–3.80)
14.2 10.9 7.3 9.3
1.07 (0.49–2.58) 1.08 (0.53–2.22) 0.87 (0.39–1.95) 1.00
14.5 11.6 11.3 9.3
1.18 (0.55–2.52) 1.20 (0.61–2.38) 1.31 (0.63–2.75) 1.00
10.9 7.7 6.3 6.8
1.02 (0.42–2.46) 0.96 (0.45–2.20) 1.02 (0.43–2.43) 1.00
15.0 10.1 11.3 7.4
1.41 (0.76–2.58) 1.07 (0.59–1.96) 1.40 (0.82–2.39) 1.00
16.4 9.8 11.5 11.7
1.04 (0.61–1.78) 0.67 (0.39–1.15) 0.92 (0.58–1.46) 1.00
11.8 7.7 7.5 6.7
1.24 (0.64–2.38) 0.92 (0.48–1.76) 1.04 (0.58–1.85) 1.00
12.4 5.5
2.13 (1.32–3.45) 1.00
14.2 4.5
3.12 (1.84–5.28) 1.00
9.5 2.9
3.42 (1.80–6.52) 1.00
7.7 9.0 18.8
1.00 1.02 (0.62–1.69) 1.93 (1.20–3.09)
6.6 12.4 20.5
1.00 1.71 (1.04–2.83) 2.83 (1.73–4.61)
4.3 7.0 15.2
1.00 1.44 (0.78–2.67) 2.92 (1.63–5.21)
10.9 11.9 10.8 10.0
1.07 (0.64–1.79) 1.58 (0.96–2.57) 1.09 (0.67–1.79) 1.00
12.1 14.0 12.3 8.9
1.37 (0.82–2.30) 1.84 (1.13–3.02) 1.36 (0.83–2.23) 1.00
8.1 9.3 7.8 6.7
1.23 (0.67–2.25) 1.87 (1.06–3.31) 1.27 (0.71–2.27) 1.00
10.6 11.0
1.15 (0.82–1.62) 1.00
11.3 12.6
1.02 (0.74–1.42) 1.00
6.9 9.0
0.90 (0.61–1.33) 1.00
5.1 11.5 25.3
1.00 2.49 (1.63–3.83) 5.98 (3.54–10.11)
5.4 12.8 28.4
1.00 2.63 (1.73–3.98) 7.81 (4.71–12.95)
3.6 8.2 20.1
1.00 2.72 (1.65–4.49) 7.94 (4.36–14.45)
a When appropriate, adjusted for age, gender, income, race, and education. aOR, adjusted odds ratio; CI, confidence interval.
Similarly, assistance in planning an exercise routine and follow-up of PA levels appear to be directed toward those whom physicians may well perceive as being more in need of exercise. The offering of assistance in planning an exercise regimen and follow-up regarding patients’ PA are both more common among those who report more chronic diseases, are older, are nonwhite, are female (for follow-up support only), or report more visits to the doctor. We explored relationships among assistance and follow-up support among those patients who had re194
ceived advice. Within this group, those reporting follow-up support were more likely to report PA, the OR for follow-up support (adjusted for age, gender, race, income, and education) was 1.83 (p⬍0.05). The results for assistance in developing an exercise plan were in the same direction, but not significant. Although limited by being cross-sectional and post-hoc, these analyses suggest that follow-up support may be important for successful behavior change. These findings and other reviews39 – 41 indicate the utility of self-management counseling and follow-up
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support in maintaining behavior change, but also the infrequency of their provision. Ongoing follow-up may be especially important in PA. For example, most individuals who quit smoking reach some point when their likelihood of relapse is low and, presumably, the effort of remaining abstinent is also low. In contrast, PA continues to require time, attention, and energy for as long as it is maintained. Ongoing support and encouragement by health professionals is likely to be helpful in maintaining it, especially as individuals age and injuries or comorbid conditions create increasing barriers to PA. Physician training programs for PA counseling need to go beyond asking a single question to include effective behavior change and maintenance strategies. Earlier studies found lower-income individuals and those with less education or on Medicaid to be less likely to receive physician advice to exercise,36,37 whereas our study did not replicate these relationships. The present finding of more frequent advice, assistance in planning, and follow-up support for minority members is, to our knowledge, unique in the literature. This bears replication in other representative studies and is encouraging regarding attempts to reduce the disparities in health and health care.1 Limitations of the current project are that it is based on self-report data and cross-sectional in design. It would have been helpful to have recorded information on the time elapsed since the last medical office visit to investigate potential recall bias issues. Prospective studies of health professionals’ advice to exercise and related interventions to promote PA are needed. These studies should include objective measures of both patient–provider interactions to promote PA (e.g., tape recordings) and of activity itself (e.g., activity monitors). In summary, the frequency with which physicians provide advice to exercise and follow-up support fails to reflect growing evidence of the importance of PA in prevention and disease management. To the extent that it is provided, advice is likely directed to those with clinical circumstances indicating a need for exercise or the possibility of benefit from it. Unfortunately, this pattern of advice overlooks the preventive role of PA.20 PA needs to join weight, blood pressure, and, more recently, smoking,42 as a vital sign conducted during routine visits. As with other behavior and education components of health care, just educating individual clinicians on recommended practice patterns is unlikely to be successful. Rather, progress will most likely follow system changes and practice redesign to encourage improved practice.43,44 In particular, ongoing attention and follow-up from health professionals may be especially helpful for PA, the benefits of which are substantial but also require maintenance for the duration of individuals’ lives.45
This study was funded through the Centers for Disease Control and Prevention, contract U48/CCU710806 (Prevention Research Centers Program), including support from the Community Prevention Study of the National Institutes of Health’s Women’s Health Initiative. Human subjects approval was obtained from the Saint Louis University Institutional Review Board. We are grateful for the assistance of Patsy Henderson, Nancy Noedel, and Mary Cregger of Battelle for assistance in data collection; Frank Markowitz of GENESYS Sampling Systems for sampling help; and Tracey Cannon and Katie Dugan of the Prevention Research Center at Saint Louis University and Barbara McCray at AMC Cancer Research Center for administrative support.
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