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Health Behavior Change Programs in Primary Care and Community Practices for Cardiovascular Disease Prevention and Risk Factor Management Among Midlife and Older Adults: A Scientific Statement From the American Heart Association

Originally published 2021;144:e533–e549


Cardiovascular disease predominates as the leading health burden among middle-aged and older American adults, but progress in improving cardiovascular health remains slow. Comprehensive, evidenced-based behavioral counseling interventions in primary care are a recommended first-line approach for promoting healthy behaviors and preventing poor cardiovascular disease outcomes in adults with cardiovascular risk factors. Assisting patients to adopt and achieve their health promotion goals and arranging follow-up support are critical tenets of the 5A Model for behavior counseling in primary care. These 2 steps in behavior counseling are considered essential to effectively promote meaningful and lasting behavior change for primary cardiovascular disease prevention. However, adoption and implementation of behavioral counseling interventions in clinical settings can be challenging. The purpose of this scientific statement from the American Heart Association is to guide primary health care professional efforts to offer or refer patients for behavioral counseling, beyond what can be done during brief and infrequent office visits. This scientific statement presents evidence of effective behavioral intervention programs that are feasible for adoption in primary care settings for cardiovascular disease prevention and risk management in middle-aged and older adults. Furthermore, examples are provided of resources available to facilitate the widespread adoption and implementation of behavioral intervention programs in primary care or community-based settings and practical approaches to appropriately engage and refer patients to these programs. In addition, current national models that influence translation of evidence-based behavioral counseling in primary care and community settings are described. Finally, this scientific statement highlights opportunities to enhance the delivery of equitable and preventive care that prioritizes effective behavioral counseling of patients with varying levels of cardiovascular disease risk.

Cardiovascular disease (CVD) remains the leading cause of death among middle-aged and older adult populations.1 Nearly a quarter of CVD deaths are avoidable with appropriate preventive health care.2,3 Evidence-based guidelines recommend behavioral counseling as the first line of treatment to promote cardiovascular health behaviors (eg, physical activity, healthy diet) and to reduce risk factors (obesity, hypertension).4–7 In these guidelines, primary health care professionals are advised to integrate behavioral counseling into primary care and to offer referrals for patients with CVD risk factors or a CVD diagnosis to evidence-based behavioral intervention programs. Grounded in theory-based behavior change principles, the 5A Model (assess, advise, agree, assist, arrange) is a clinical framework that guides the process of brief and focused behavior counseling in clinical settings.7 However, short, episodic office visits typical of busy clinical settings are not conducive to effective evidence-based behavioral counseling. Effective counseling typically requires multiple structured visits to deliver a behavior change theory–driven comprehensive, multicomponent intervention program. Most important to effectively operationalizing the 5A Model is the ability to assist patients in setting health behavior goals and to arrange follow-up support in which health care professionals can refer patients to evidence-based behavioral counseling programs in primary care or community settings.

This scientific statement presents evidence of effective behavioral intervention programs that are feasible for adoption in primary care settings for CVD prevention and risk management in midlife and older adult populations. The purpose of this scientific statement is to help guide health care professionals’ efforts to offer or refer patients for behavioral counseling, beyond what can be done during brief and infrequent office visits, and to promote meaningful and lasting behavior change for CVD prevention among midlife and older adults. An additional objective is to inform health care professionals of resources that facilitate widespread adoption of behavioral intervention programs within primary care settings or implementation into community-based settings. The scientific statement also examines the accessibility of these programs using team-based care and referral schemes to appropriately route patients. Furthermore, this scientific statement reviews the impact of existing models implemented nationally in the United States both to enhance the translation of evidence-based behavioral counseling in primary care and community settings and to encourage delivery of equitable and preventive care to patients with varying levels of CVD risk. Lessons learned from this scientific statement could inform US-based clinical practice.

Literature Search Methodology

An empirical approach to identify the included randomized clinical trials was used to generate this scientific statement. With the use of a review-of-reviews methodology, meta-analyses and systematic reviews of primary care feasible intervention trials published from January 2005 through July 2020 were identified. Earlier publications were also considered to address subquestions or to capture historic landmark studies. This search strategy included searches of MEDLINE, PubMed, Web of Science, and the Cochrane Central Register of Controlled Trials, with all searches limited to articles published in the English language. Further examinations of reference lists of other previously published reviews, meta-analyses, and primary studies and from the US Preventive Services Task Force were conducted to identify potential studies for inclusion. This statement included randomized clinical trials of behavioral counseling interventions on diet and nutrition, physical activity (PA), or a combination thereof that were conducted in midlife (40–64 years of age) and older (≥65 years of age) adult populations with increased risk of CVD. Included intervention trials were tested in primary care settings or demonstrated feasibility for implementation in a primary care setting (eg, the interventions that could be “referable” from primary care and implemented in a community-based practice health care system) and had a minimal follow-up time of 6 months after baseline for outcome assessment. Intervention trials with a primary aim of weight loss were included if the study targeted populations with CVD risk factors and involved a behavior counseling intervention. Likewise, studies with known diabetes were included if the primary aim of the intervention was to improve cardiovascular health (ie, cardiovascular risk behaviors or risk factors). Excluded intervention trials were those that did not include a randomized trial design, had limited generalizability to primary care (eg, emergency departments, inpatient hospital settings, ambulatory facilities, nursing homes/other institutional settings, and occupational settings), or had limited feasibility for implementation in primary care or community health care settings (eg, environmental interventions, public policy interventions).

Evidence and Effectiveness of Health Behavior Change Interventions Tested in Primary Care and Community-Based Settings

Broadscale delivery and implementation of evidence-based health behavior interventions by primary care professionals and other health care team members have become much more feasible over the past decade with the expanded focus of health care systems on prioritizing accountable care and population health management.8 In this respect, the primary care setting can strategically function as a gateway for connecting patients with clinic-community partnerships that offer multifaceted behavioral intervention programs to promote favorable, lasting changes in health risk behaviors and potentially to improve CVD risk factors (eg, blood pressure, adverse lipid profiles).7,9 Contemporary approaches to addressing risk behaviors in primary care settings focus on incremental interventions targeting specific nutritional components or dietary patterns, PA, or some combination thereof to reduce CVD risk. In this section, the effectiveness of select behavior counseling intervention programs, delivered in primary care or referred from primary care settings, in improving 1 or more of these cardiovascular risk behaviors or risk factors is discussed.

Behavior Change Interventions on Diet and Nutrition

Modifications in dietary behavior are influenced by myriad complex factors, including early life experiences, socioeconomic status, and food policy.10 Research reviews on interventions aimed at diet or nutrition change report that multicomponent, high-intensity, low-reach interventions may be effective at promoting clinically meaningful and sustained dietary habits (Table 1). For example, the landmark PREDIMED trial (Prevención con Dieta Mediterránea)11,12 delivered multiple sessions of education and patient-centered counseling support. In addition to being provided nuts or olive oil to support a Mediterranean diet, both intervention groups underwent a dietary assessment followed by a meeting with a registered dietician to discuss individual recommendations to help adopt the Mediterranean diet. At study inclusion and quarterly thereafter, participants attended 60-minute group educational sessions (20 sessions total) that reviewed dietary goals, meal plans, and shopping list and answered questions about the recommended diet; participants received free supplemental food, depending on group assignment. During quarterly visits with the registered dietician, participant progress was assessed, and dietary goals were re-evaluated and modified as needed. Personalized dietary counseling also was offered to intervention participants to assist their efforts in meeting dietary goals. Registered dieticians used several cognitive behavioral techniques such as goal setting, self-monitoring, feedback and reinforcement, self-efficacy enhancement, incentives, problem solving, and relapse prevention delivered with a motivational interviewing counseling style. In contrast, control participants received a brief counseling session along with annual brochures that emphasized a low-fat Mediterranean diet. However, in the fourth year of the study and beyond, control participants received quarterly invitations to individual and group educational sessions that emphasized healthy low-fat foods. In this large sample of >7000 participants at high risk of CVD, the intervention resulted in reductions in the incidence of major cardiovascular events. Given that PREDIMED was evaluated in the context of a Mediterranean culture and involved the provision of food (oil and nuts) to participants, caution is advised with respect to the generalizability of the findings. On the other hand, the behavioral counseling approaches used in this study have good cross-cultural acceptability and can be used to encourage patients to move toward a healthy Mediterranean-style eating pattern, consistent with the current dietary guidelines.16

Table 1. Behavior Change Interventions Targeting Diet or Nutrient Quality

ReferenceParticipants characteristics, mean change or %Intervention deliveryMain outcomes, mean change
Age, yFemale, %White, %BMI,kg/m2Delivery modeInterventionistDuration, mo, and dose, n sessionsWeight loss, kgBP, mm HgPADietRetention, %
PREDIMED trial, 2014 (BP)11* (N=280)
1: Mediterranean diet with EVOO (n=88)
2: Mediterranean diet with nuts (n=95)
3: Low-fat (control diet; n=97)
1: 66.2
2: 67.2
3: 66.2
1: 57.7
2: 53.7
3: 57.3
NR1: 29.5
2: 30.3
3: 30.4
1: Group +individual
2: Group+individual
3: Group+individual
RDsDuration: 12
Dose: A dietitian-led motivational and education intervention including both individual and group sessions every 3 mo
1: −2.3
2: −2.6
3: 1.7
1: −1.2
2: −1.2
3: 0.7
NRNR1: 88.6
2: 86.3
3: 77.3
PREDIMED trial, 201912* (body weight; N=7447)
1: Mediterranean diet with EVOO (n=2543)
2: Mediterranean diet with nuts (n=2454)
3: Low fat (control diet; n=2450)
1: 66.7
2: 67.0
3: 67.3
2: 41
3: 60
NR1: 29.7
2: 29.9
3: 30.2
1: Group+individual
2: Group+individual
3: Group+individual
RDsDuration: 12 with median follow-up of 4.8 y
Dose: A dietitian-led motivational and education intervention including both individual and group sessions every 3 mo
1: −0.880
2: −0.402
3: −0.604
NRNRNR1: 59.0
2: 50.5
3: 50.7
Track trial, 201913 (N=306)
1: Usual care (n=150)
2: Weight loss (n=127)
1: 50.5
2: 50.9
1: 68
2: 68
1: 31
2: 29
1: 35.9
2: 35.9
1: Individual
2: Individual/app/telephone
Duration: 12
Dose: Daily app, 18 dietician calls, 3 physician counseling appointments (baseline, 6 mo, 12 mo)
1: −0.01
2: −1.4
1: −7.5
2: −8.4
1: −4.2
2: −5.2
NRDASH nutrients score:
 1: 0.20
 2: 1.28
1: 91.4
2: 88.6
Sacerdote et al,14 2006* (N=3179)
1: Personalized nutrition with brochure (n=1592)
2: Nonpersonalized sham intervention (n=1587)
1: 44.7
2: 44.2
1: 50.0
2: 49.9
NR1: 24.8
2: 24.3
1: Individual
2: Individual
GPsDuration: 12
Dose: At baseline, a GP administered 15-min personalized nutritional intervention based on a brochure about diet and health (provided to participants) that was focused on the importance of higher consumption of fruits, vegetables, fish, and olive oil and lower consumption of red meat, snacks, and sweets
BMI change: 1: −0.412: 0SBP:
1: 15
2: −0.20
1: 0.44
2: 0.61
NR>35 servings of fruits and vegetables per week:
 1: 2.89
 2: 1.58
≥1 serving of fish per week:
 1: 0.4 2: 0.16
<3 servings of red meat per week:
 1: −0.47
 2: −0.22
Use of olive oil:
 1: 0.37
 2: 0.22
1: 93.4
2: 93.8
Rural Physician Cancer Prevention Project15 (N=754)
1: Tailored feedback, telephone counseling, booklets (n=377)
2: Usual care (n=377)
1: 47.9
2: 47.8
1: 65.8
2: 65.0
1: 60.5
2: 60.7
NR1: Individual
2: Individual
NRDuration: 12
Dose: 1 Baseline personalized feedback mailer based on fat and fiber intake (assessed by questionnaire) that used stoplight metaphor (stop, yield, go), 1 telephone call 2 wk after feedback designed to answer questions from participants with lower literacy, 5 booklets reviewing behaviors and skills associated with healthy eating mailed weekly (in staggered format) after the call
NRNRNRDietary fat behavior:
 1: 1.87 2: 1.95
Dietary fiber behavior:
 1: 12
 2: 16
Fat knowledge:
 1: 5.59
 2: 5.58
Self-efficacy fat:
 1: 1.82
 2: 1.86
Intentions fat:
 1: 3.63 2: 3.40
Intentions fiber:
 1: 3.32 2: 3.07
1: 73.7
2: 63.1

This table includes examples of studies and does not represent a complete list. Duration indicates number of intervention months. Dose represents the number of touch points during the intervention with the interventionist.

App indicates application; BMI, body mass index; BP, blood pressure; DASH, Dietary Approaches to Stop Hypertension; DBP, diastolic blood pressure; EVOO, extravirgin olive oil; GP, general practitioner; NR, not reported; PA, physical activity; PREDIMED, Prevención con Dieta Mediterránea; RD, registered dietician; and SBP, systolic blood pressure.

* Studies conducted outside of the United States.

† Statistically significant group difference.

Similar to PREDIMED, the Track study was another intensive randomized controlled trial of a 12-month weight loss intervention for patients with obesity at a community health center, most of whom had a diagnosis of hypertension, diabetes, or hyperlipidemia.13 The intervention consisted of algorithm-generated tailored behavior change goals (eg, no sugary drinks, walking 10 000 steps per day, no fast food, no salty snacks). Other behavior change components included self-monitoring of these goals via mobile technologies, weighing daily on a network-connected scale, skills training materials, 18 weight loss coaching telephone calls with a Track registered dietician, and weight loss counseling by physicians trained in motivational communication. This multicomponent intervention produced significant weight loss and small improvements in DASH (Dietary Approaches to Stop Hypertension) diet adherence.

In an effort to address the realities of time constraints and limitations in professional training in real-world, primary care settings, an Italian randomized controlled trial14 of a nonstructured brief educational nutritional intervention was conducted. On completing a food frequency questionnaire, heathy adult participants received a 15-minute personalized nutrition intervention based on a brochure about healthy dietary habits delivered by general practitioners. This brief intervention resulted in multiple improvements in diet (reduced intake of meat and increased intake of fruits and vegetables, fish, and olive oil) and reductions in body mass index relative to a sham control condition. Similarly, to reach under-resourced populations, the Rural Physician Cancer Prevention Project15 evaluated the impact of a low-intensity, health care professional–endorsed self-help dietary intervention that provided tailored dietary feedback to promote improved fat and fiber intake in a rural, low-socioeconomic-status, partly underrepresented population. After a baseline interview with trained staff, which included a questionnaire on dietary fat and fiber eating behaviors, participants received personalized feedback packets on fat and fiber intakes that were based on their baseline scores. Consistent with best practices in behavioral trial design,17 feedback messages were developed by nutrition experts and designed with a theory-driven, evidence-based model to develop a health literacy–appropriate car-racing theme that was tailored to the rural target population. For example, participants were provided “stop” (poor eating habits), “yield” (needs improvement), or “go” (good habits) feedback messages for fat and fiber intake with accompanying recommendations on each. A structured telephone call with brief counseling was also administered by trained staff to participants, followed by weekly mailings of self-help booklets (5 total) that focused on behaviors and skills associated with healthy eating (eg, nutrition label reading, realistic goal setting, recipe modifications). Overall, participants in the intervention reported small but significant improvements in fat and fiber intake at the 1-, 6-, and 12-month follow-ups. This has been characterized as a low-intensity success given that primary care professionals’ commitment was only to provide endorsement by signing the intervention feedback letters.

In summary, findings from these reviewed trials support the use of brief, theory-driven, evidence-based, competency-based dietary interventional approaches focusing on dietary patterns, which is consistent with contemporary dietary guidelines.16

Behavior Change Interventions Promoting PA

An overwhelming body of literature supports the positive cardiometabolic health effects of PA performed at nationally recommended levels.18 Empirical evidence identifying the benefits of PA has come largely from well-controlled intervention trials that typically deliver the stimulus (ie, aerobic or resistance exercise) in a laboratory setting, with continuous supervision, guidance, and often financial compensation for study participation. Although this controlled scientific approach rigorously tests the efficacy of a particular intervention, subsequent translation to a real-world application may be challenging for middle-aged or older adults unaccustomed to an active lifestyle. Accordingly, annual or more frequent appointments with primary care professionals are ideal settings for patients to receive health-related education and support services related to PA.18 However, limited face-to-face time between health care professionals and patients reduces the likelihood of effective counseling and PA adoption. Therefore, investigators have sought to optimize the strategy of delivering PA interventions within the primary care setting.

Among the studies described in Table 2, it is evident that patients randomized to receive standard care (ie, ≈5 minutes of education delivered by a physician within a clinical visit) were less likely to increase PA levels compared with individuals in the intervention groups. Furthermore, interventions that provided informational packets or newsletters in addition to physician-delivered verbal PA recommendations were inadequate in increasing PA. Studies that incorporated a greater number of patient encounters with professionals specializing in PA guidance (eg, exercise physiologists, physical therapists) and implemented evidence-based approaches to increasing PA were more successful. For instance, the use of pedometers for self-assessing and -monitoring daily PA19,20 or motivational interviewing and cognitive behavior theories that facilitate goal setting and overcoming barriers contributed to significant increases in steps,19,20 device-measured PA time,20 or self-reported PA time.20–25,28 The majority of studies had small changes in body mass index, ranging from −0.11 to −0.03 kg/m2 at 12 months after intervention.20,22,26,27 However, 1 study using an exercise specialist to guide group-based PA sessions resulted in a decrease in almost 1 body mass index unit at the end of 6 months (−0.93 kg/m2).19

Table 2. Behavior Change Intervention Promoting PA

ReferenceParticipants characteristics, mean change or %Intervention deliveryMain outcomes, mean change
Age, yFemale, %White, %BMI,kg/m2DeliverymodeInterventionistDuration, mo, and dose, n sessionsWeight loss, kgBP, mm HgPADietRetention, %
HEALD Intervention, 201519* (N=198)
1: Intervention (n=102)
2: Control (n=96)
5951NR1: 34.6
2: 32.5
1: In-person+pedometer
2: Pedometer
Exercise specialistDuration: 6
 1: Group exercise sessions on weeks 1 and 2; 2 group exercise sessions on weeks 13 and 14
 2: Given pedometer with no instructions and no in-person sessions
1: 14812: 336
NR1: 67
2: 83
PACE-UP20* (N=1023)
1: Nurse (n=346)
2: Postal (n=339)
3: Control (n=338)
45–756477NR1: In-person
2: Mail
3: Usual care
NurseDuration: 12
 1: First visit provided pedometer with instructions; additional in-person consultations at weeks 1 (30 min), 5 (20 min), and 9 (20 min)
 2: Pedometer provided with instructions via mail
 3: Usual care
1 vs 3: −0.03
2 vs 3: −0.1
NRPA time
1 vs 3: 352 vs 3: 33
NR1: 92
2: 92
3: 95
Pinto et al,21 2005 (N=100)
1: Intervention (n=52)
2: Brief advice (n=48)
6863851: 29.2
2: 28.2
1: In-person and telephone
2: In-person
Health educatorsDuration: 3
 1: 3 Face-to-face PA counseling sessions (mo 0, 1, and 3 for 30–45 min); 12 PA counseling telephone calls (weekly first 3 mo, then every other wk for second 3 mo lasting 10–15 min)
 2: 1 In-person advice session (3–5 min)
NRNRMod PA, min
1: 62.82: 16.6
NR1: 92
2: 96
Step Test Exercise Prescription Stages, 201022* (N=360)
1: Intervention (n=193)
2: Control (n=167)
6552NR1: 26.6
2: 29.1
1: In-person
2: In-person
PhysicianDuration: 12
 1: PA counseling at baseline and 3 and 6 mo
 2: Initial PA prescription followed by usual care visits
1: 0.13
2: −0.17
1: -4.132: -0.38Daily energy expenditure, cal/d
1: 692: −7
WISEWOMAN, 201223 (N=1093)
1: Intervention (n=552)
2: Usual care (n=541)
5210035NRIn-personCommunity health workersDuration: 6
 1: 3 Counseling sessions of 50 min at 1, 2, and 6 mo after screening
 2: Usual care
NRNROdds ratio Reported Mod PA
1: 2.192: 1.10
Vig PA
1: 3.372: 1.11
PEPAF trial, 201724* (N=4317)
1: Intervention (n=2248)
2: Usual care (n=2069)
5065NRNRIn-personPhysicianDuration: 6
 1: 1 PA prescription and advice for 15 min
 2: Standard care
NRNRReported PA, min/wk
1: 18
ACT, 200125 (N=874)
1: Advice (n=292)
2: Assistance (n=293)
3: Advice+assistance (n=289)
5145711: 30.0
2: 29.0
3: 30.0
1: In-person
2: In-person, telephone, mail
3: In-person, telephone, mail
1: Physician
2: Physician+health educators
3: Physician+health educators
Duration: 24
 1: PA advice during 3 physician visits
 2: Initial 30- to 40-min counseling session
Contacts for women and men:
2.1 and 3.1 individual visits; 3.8 and 2.9 telephone calls; 14.8 and 16 monthly tailored newsletters Total contacts, 21.7 and 22
3: Same intervention as 2 but more frequent telephone contacts
Contacts for women and men:
3.7 and 3.0 individual visits; 21.0 and 19.4 telephone calls; 15.1 and 14.55 newsletters
NRNRNo significant change across groupsNR1: 91
2: 94
3: 90
CHIP, 201026 (N=394)
1: Intervention (n=187)
2: Usual care (n=207)
4669411: 30.7
2: 30.0
1: Mailed message1: Research staffDuration: 6
 1: PA promotional mail sent at baseline and 1, 3, and 6 mo
 2: Received information on recommended preventive tests at baseline and 1, 3, and 6 mo
NRNRTotal PA, min
1: 133
2: 99
NR1: 88
2: 90
Green Prescription Program, 200527* (N=270)
1: Intervention (n=130)
2: Usual care (n=140)
7163NRNR1: In-person and telephone1: Physician or nurse and exercise specialistDuration: 12
 1: 1 brief activity counseling session followed by 3 telephone support sessions
 2: Usual care
NR−0.56PA, h/wk
1: 0.67
Christian et al,28 2008 (N=310)
1: Intervention (n=155)
2: Usual care (n=155)
536601: 35.4
2: 34.8
1: In-person
2: Educational material
1: Computer-based assessment and physician1: Review of tailored lifestyle change goals at baseline and 3, 6, and 9 mo
2: Usual care visits at baseline and 3, 6, and 9 mo
Weight, lb
1: −0.8±10.92
2: 1.39±0.60
1: −2.55±20.37
2: −4.66±20.81
1: 354±5742: 51±443
NR1: 90.9
2: 85.2

This table includes examples of studies and does not represent a complete list. Duration indicates number of intervention months. Dose represents the number of touch points during the intervention with the interventionist.

ACT indicates Activity Counseling Trial; BMI, body mass index; BP, blood pressure; CHIP, Computerized Health Improvement Project; HEALD, Health Eating and Active Living for Diabetes; MET, metabolic equivalent of task; Mod, moderate intensity; NR, not reported; PA, physical activity; PACE-UP, Pedometer and Consultation Evaluation; PEPAF, Experimental Program for Physical Activity Promotion; and Vig, vigorous intensity.

* Studies conducted outside of the United States.

† Statistically significant group difference.

Behavior Change Interventions on Diet and PA

Multicomponent behavioral interventions targeting diet and PA have demonstrated similar success in sustaining long-term improvements in cardiovascular risk factors in various high-risk populations (Table 3). The majority of interventions were led by nonphysicians (ie, registered dietitians, diabetes/health educators) in parallel with clinic visits with a primary care professional. With this combined approach (ie, non–primary care professional delivering the intervention during routine clinic visits), delivery of the intervention does not add substantial time from the primary care professional directly.

Table 3. Multicomponent Behavior Change Interventions Targeting Diet and PA

ReferenceParticipants characteristics, mean change or %Intervention deliveryMain outcomes, mean change
Age, yFemale, %White, %BMI,kg/m2Delivery modeInterventionistDuration, mo, and dose, n sessionsWeight loss, kgBP, mm HgPADietRetention, %
201729 (N=894)
1: Telehealth (n=256)
2: In-person (n=638)
5284NR1: 35.8
2: 36.4
1: Virtual
2: In-person
Lifestyle coach (RD, diabetes educator, or athletic trainer)Duration: 4
16 group sessions weekly
1: −5.5
2: −6.0
2: 96
E-LITE, 201330 (N=241)
1: Remote self-directed videos (n=81)
2: In-person (n=79)
3: Usual care (n=81)
53477832.01: Virtual
2: In-person
3: Usual care
RD and fitness instructorDuration: 15
 3-mo intensive (12 weekly) followed by 12-mo (monthly individual feedback) maintenance phase
1: −4.52: −6.33: −2.4SBP:
1: −0.4
2: −1.2
3: 0.1
1: −1.1
2: −1.9
3: −0.3
NRNR1: 93
2: 91
3: 91
Be Fit, Be Well, 201231 (N=365)
1: Intervention (n=180)
2: Usual care
5569291: 37.0
2: 37.0
1: Virtual
2: Telephone
Health educatorsDuration: 24
 Monthly 15- to 20-min calls first year, bimonthly (ie, every other month) second year (18 total scheduled calls)
1: −1.5
2: −0.5
1: 1.8
2: 4.3DBP
1: 0.6
2: 2.0
NRNR1: 82
2: 90
REACH, 201832* (N=264)
1: E-counseling (n=133)
2: Control (n=131)
1: 58
2: 57
1: 61
2: 56
NR1: 31.5
2: 30.7
1: Virtual/in-person
2: In-person
Health care professionals and peers featured in videosDuration: 12
 Weekly emails mo 1–4, biweekly mo 5–8, and monthly mo 9–12
1: −10.12: −6.0
1: −4.9
2: −3.5
NRNR1: 75
2: 74
Well-Telehealth, 201833 (N=351)
1: Intervention (n=176)
2: Usual care (n=175)
5168561: 35.9
2: 35.9
1: App and telephone
2: In-person
PCP (median, 3 visits)
Duration: 12
 18 Coaching calls (10–15 min) over 12 mo
1: −4.02: −0.1SBP
1: −8.4
2: −7.5
1: −5.2
2: −4.2
NRNR1: 89
2: 91
POWER, 201134 (N=415)
1: Remote (n=138)
2: In-person (n=139)
3: Usual care (n=138)
5463561: 36.0
2: 36.8
3: 36.6
1: Telephone
2: In-person
3: Usual care
PCP (median, 1 visit)
Duration: 24
 1: 20-min telephone calls for 12 wk
 2: 90-min group sessions for 9 wk and 20-min telephone calls for 3 wk
1: −4.62: −5.13: −1.4NRNRNR1: 77
2: 74
3: 67
POWER-UP, 201135 (N=390)
1: Enhanced in-person (n=129)
2: In-person (n=131)
3: Usual care (n=130)
528059391: In-person
2: In-person
3: Usual care
Lifestyle coach (medical assistant)
Duration: 24
 Quarterly visits with PCP (all), 10–15 min/mo with lifestyle coach (brief+enhanced)
1: −4.62: −2.93: −1.7NRNRNR1: 88
2: 85
3: 85
ADAPT, 200736* (N=241)
1: In-person (n=123)
2: Usual care (n=118)
1: 57
2: 55
1: 67
2: 67
NR1: 30.4
2: 29.7
1: In-person
2: Usual care
RDDuration: 12
 6 Group sessions
1: −3.92: −1.4NRNREnergy intake, MJ:
1: −1.32: −0.8
Total fat, % energy:
1: −3.62: −0.3
1: 83
2: 76
PREMIER, 200637 (N=810)
1: Advice only (n=273)
2: Established (n=268)
3: Established+DASH (n=269)
1: 50
2: 50
3: 50
1: 63
2: 65
3: 57
1: 61
2: 61
3: 67
1: 32.9
2: 33.0
3: 33.3
1: In-person
2: Group+individual
3: Group+individual
RD or health educatorsDuration: 18
 1: Advice only: 2 individual sessions for 30 min
 2 and 3: 14 Group sessions+4 individual sessions for 6 mo; monthly group sessions+3 individual counseling sessions for 12 mo
1: −1.5
2: −3.8
3: −4.3
NREnergy expenditure, kcal/kg
1: 0.6
2: 0.3
3: 0.8
Total fat,
% energy:
1: −1.02: −3.0
3: −7.4
1: 94
2: 93
3: 96
HIP, 200938 (N=574)
MD Control
1: Control (n=141)
2: Intervention (n=140)
MD Intervention
3: Control (n=148)
4: Intervention (n=145)
1: 61
2: 59
3: 62
4: 61
1: 65
2: 66
3: 58
4: 55
NR1: 32.9
2: 31.8
3: 32.7
4: 32.6
MD intervention was provided online (and provided CME credit)Behavioral interventionistDuration: 18
 20 Group sessions over 6 mo followed by 12 monthly calls
Weight, lb
1: −2.1
2: −2.6
3: −0.4
4: −3.8
1: −13.0
2: −21.5
3: 5.0
4: −0.7
Total fat, %kcal:
1: 0.8
2: −1.7
3: −1.1
4: −2.8
1: 87
2: 89
3: 91
4: 88
Martin et al,39 2008 (N=144)
1: Intervention (n=68)
2: Standard care (n=69)
1: 41
2: 43
10001: 38.3
2: 39.8
In-personPhysicianDuration: 5
 Monthly meetings for 15 min with physician
1: −1.52
2: 0.61
HHER trial, 201140 (N=266)
1: Intervention (n=136)
2: Standard care (n=130)
NR1000NRTelephonecallsNurseDuration: 12
 Monthly newsletters+up to 14 tailored counseling Telephone calls for 1 y
1: –7.162: –3.37
1: –3.322: –0.90
Side dishes/snacks:
1: 0.35
2: 1.06
Dairy products:
1: –2.062: –1.72
Spreads, dressings, and oils:
1: –3.43
2: –3.21
1: 60
2: 54
HELP, 200541 (N=237)
1: Group classes (n=43)
2: Self-help (n=43)
3: Clinical visits only (n=42)
43.591038.0All: Weekly in-person sessions (10 wk)
1: Group classes
2: Literature
3: Standard care visits
RD, fitness educators, or behavioral interventionistsDuration: 18
 10 weekly 75-min sessions (group classes)
 Ad hoc HELP line (self-help group)
1: −0.08
2: −1.3
3: −1.4
2: 65
3: 74
PHP, 200542 (N=154)
1: Intervention (n=77)
2: Usual care (n=77)
1: 52.2
2: 53.4
1: 82
2: 79
1: 78
2: 75
1: 33.3
2: 34.1
Group meetings and individual telephone callsHealth coachDuration: 10
 Group sessions for 2 h (28 sessions over 10 mo); individual sessions with coach by telephone every 2 wk (20–30 min)
1: −1.2
2: −0.6
2: 86

This table includes examples of studies and does not represent a complete list.

Duration indicates number of intervention months. Dose represents the number of touch points during intervention with interventionist.

ADAPT indicates Activity, Diet, and Blood Pressure Trial; App, application; BMI, body mass index; BP, blood pressure; DASH, Dietary Approaches to Stop Hypertension; DBP, diastolic blood pressure; DPP, Diabetes Prevention Program; DRA, Dietary Risk Assessment; E-LITE, Evaluation of Lifestyle Interventions to Treat Elevated Cardiometabolic Risk in Primary Care; HELP, Healthy Eating and Lifestyle Program; HHER, Heart Healthy & Ethnically Relevant Lifestyle; HIP, Hypertension Improvement Project; MVPA, moderate-vigorous physical activity; NR, not reported; PA, physical activity; PCP, primary care physician; PHP, Personalized Health Plan; PREMIER, Lifestyle Interventions for Blood Pressure Control; POWER, Practice-Based Opportunities for Weight Reduction; POWER-UP, Practice-Based Opportunities for Weight Reduction Trial at the University of Pennsylvania; RD, registered dietitian; REACH, e-Counseling Promotes Blood Pressure Reduction and Therapeutic Lifestyle Change in Hypertension; and SBP, systolic blood pressure.

* Studies conducted outside of the United States.

† Statistically significant group difference.

Numerous interventions adapted the Diabetes Prevention Program (DPP) curriculum and were led via in-person or virtual (via telephone or computer) sessions.29 Vadheim et al29 compared an in-person DPP intervention with an adapted telehealth intervention and found that both resulted in substantial weight loss at the end of 1 year (−5.5 lb for the telehealth versus −6.0 lb for the in-person intervention) with no additional visits to the primary care professional. Ma et al30 examined various adaptations of the delivery of the original DPP curriculum, including a coach-led group intervention (registered dietitian plus fitness instructor), versus a self-directed DVD intervention in the E-LITE trial (Evaluation of Lifestyle Interventions to Treat Elevated Cardiometabolic Risk in Primary Care). Although all participants lost weight at the end of the 15-month intervention, the coach-led group lost the most weight (−6.3 lb), followed by the self-directed group (−4.5 lb), compared with the usual care group (−2.4 lb). Accordingly, most interventions targeted weight loss outcomes; however, a few were focused on decreasing blood pressure outcomes as well. Be Fit, Be Well was a 2-year virtual intervention focused on weight loss and hypertension self-management through tailored goals, self-monitoring, and skills training.31 Compared with the groups who received usual care, individuals receiving the behavioral intervention were more likely to maintain their blood pressure throughout the 2-year study (1.8 mm Hg versus 4.3 mm Hg in systolic blood pressure; P=0.02). Similar results were found by Nolan et al32 in the REACH (e-Counseling Promotes Blood Pressure Reduction and Therapeutic Lifestyle Change in Hypertension) intervention. Participants in the behavioral intervention condition significantly decreased their systolic blood pressure compared with the usual care group (−10.1 mm Hg versus −6.0 mm Hg; P=0.02).

Increasing evidence suggests that primary care models offering comprehensive behavior counseling interventions may be effective at improving cardiovascular health in underrepresented populations, including those specifically targeting women and low-income minority populations.39–42 The Heart Healthy and Ethnically Relevant Lifestyle trial40 was carried out among 266 underrepresented African American women at local community health care centers. Participants first met with a primary care professional for individual, stage-based counseling and goal setting and then were provided with monthly motivationally tailored telephone counseling sessions for 12 months. This intervention focused on increasing moderate to vigorous PA and reducing dietary fat intake, with follow-up assessed at 6 and 12 months. Compared with participants randomized to the standard care group, participants receiving the intervention demonstrated significant increases in leisure-time PA at 6 months (odds ratio, 3.82 [95% CI, 1.41–10.30]), but no differences were reported at the 12-month follow-up. In both the intervention and standard care groups, appreciable improvements in diet, as indicated by a reduction in total dietary risk assessment scores, were observed at 6 months and maintained at 12 months, with improvements being consistently and significantly larger among participants receiving the intervention (−7.16 versus −3.37 in the standard care group; P<0.001). Specifically, greater reductions in dietary fat from meat sources (−3.32 versus −0.90; P<0.001) and dairy products and eggs (−2.06 versus −1.72; P=0.04) over the 12 months were observed in participants receiving the intervention than in participants receiving standard care. Factors associated with dietary improvements included intensive telephone counseling and use of tailored materials. Consistently, in other trials of low-income populations, intervention features such as self-monitoring, targeting multiple behaviors, instruction or delivery through personal contact, and continued treatment contacts were associated with greater intervention effectiveness and long-term maintenance of health behavior improvements.39,41

In summary, health behavioral change programs conducted in primary care settings have demonstrated effectiveness in reducing body weight and blood pressure and increasing healthy components of both diet and PA with little additional burden on the primary care professional. To facilitate behavioral change action plans, primary care professionals require assistance from a registered dietitian or health coach (ie, diabetes educator, medical assistant, exercise physiologist, fitness coaches). With support from other health care professionals to deliver patient-centered intensive behavioral counseling, this approach is more feasible and conducive to producing desirable outcomes. The use of additional health care professionals facilitates important improvements in health behaviors and reduces risk factors related to CVD through both weight loss and decreases in blood pressure.

Evidence for Adoption and Implementation in Health CARE– AND Community-Based Settings

Clinicians can play a key role in behavior change for their patients but often find it difficult to effectively deliver all aspects of behavior modification therapies.43 Therefore, clinicians must frequently facilitate patients’ participation in lifestyle modification programs outside of regular clinic visits, often extending beyond traditional clinical settings. Prior research has elucidated multiple principles and strategies for the delivery of behavior change interventions. For example, evidence-based weight-loss guidelines recommend monthly interactions over a minimum of 12 months to facilitate weight loss.44 Behavior change intervention programs are most effective when patients interact, by telephone or in person, with trained interventionists in a joint effort to reach individualized behavior change goals.44 However, these effective, although intense, behavioral change programs may be less accessible in traditional clinical settings. Therefore, long-term educational and training interventions with patients often are most feasibly delivered in established community-based settings such as places of worship, senior centers, and fitness centers.45,46

The DPP is an example of a validated practice- and community-based program aimed at healthy behavior change. The DPP, now tested in multiple populations in multiple settings, has reliably demonstrated slowed progression to diabetes among those with prediabetes, achieving 5% to 7% weight loss through diet and PA.47 Moreover, the DPP leads to improvements in quality of life and has been shown to be cost-effective.47 Integrating the DPP into existing clinical offices requires optimizing health care professionals’ knowledge of recommended screening guidelines for prediabetes and their ability to identify local certified DPP programs as referral options for qualifying patients. The Centers for Disease Control and Prevention hosts an online registry of all recognized DPPs by city and state.48 Community-based locations such as YMCAs host many of these DPPs. The illustrative list below includes examples of available resources or guidance for identifying community resources for clinicians interested in referring patients to counseling and support for lifestyle modification for the prevention of CVD.

  • Centers for Disease Control and Prevention, DPP, Registry of All Recognized Organizations48

  • YMCA registry for participating locations hosting DPP49

  • Agency for Healthcare Research and Quality toolkit for linking primary care practices to local resources to manage obesity50

  • Community Preventive Services Task Force community guide for CVD51

Elements of these resources (eg, program accreditation, eligibility for insurance reimbursement) may vary by state or more local jurisdictions. Once available resources are identified, clinics can choose a real-time, point-of-care referral approach, a retrospective approach using electronic medical record or other clinic population–level data, or a combination of the 2 approaches.47

The Agency for Healthcare Research and Quality has created an extensively detailed toolkit to guide clinical practices through the steps of assessing patients, beginning to promote behavior change in clinic, and identifying suitable community-based partners to provide behavior change programs.50 Recognizing that many clinicians may lack formal training in promoting behavior change, the toolkit provides general guidance and actual scripts for health care professionals to engage patients in motivational interviewing and actively weighing the pros and cons of behavior change.50 The toolkit also details additional practical steps such as creating referral processes, educating patients about community partnerships, and informing clinicians once patients have interacted with community partners.50 Evaluating the clinical impact of behavior change is also an essential feature of any behavior change program. The Million Hearts prevention program, initiated by the US Department of Health and Human Services in partnership with the American Heart Association and the American College of Cardiology, was created to prevent 1 million heart attacks and strokes through public health and health care strategies.52 The program provides an online tool for baseline CVD risk assessment and the assessment of risk reduction achieved with the implementation of individual or combinations of medical therapies and smoking cessation.52 The inclusion of smoking cessation is helpful for this important lifestyle change, but comparable evidence-based risk reduction estimators are needed for other forms of lifestyle modification.

Working beyond individual clinics, the Centers for Disease Control and Prevention has sought to make general diabetes self-management education and support programs more accessible to all individuals diagnosed with diabetes.53 Because individual clinics may not be able to provide sufficient self-management education, the Centers for Disease Control and Prevention coordinated with all 50 state health departments and the District of Columbia to expand access to education programs to community-based, nonclinical locations such as worksites or faith-based organizations.53 The accessibility of these education programs outside of traditional clinical settings in more familiar community-based locations has been a key asset to referring and engaging more patients.

The accessibility of community-based locations for any behavior change program is significant, but both the delivery and the content of programs are also essential for success. Community health workers or promotores de salud are trained laypeople who often share the same cultural framework and life experiences as patients. Working with clinicians, community health workers can provide complementary behavior change education and training for patients in a manner that bridges frequently encountered communication gaps between clinicians and patients.45 Nation-level (eg, National Heart, Lung, and Blood Institute) and state-level organizations have created detailed training curricula for laypeople to engage local patient populations, particularly underrepresented racial and ethnic groups, in healthy behavior change.45,54 Similarly, program content and teaching approaches also need to be culturally tailored and linguistically appropriate to adequately meet the needs of diverse groups.53 Finally, the practical challenges such as transportation and scheduling required for program participation have to be addressed, particularly for those with limited financial means. Ignoring any of these considerations potentially widens existing disparities between majority groups and groups traditionally under-resourced with respect to access and quality of health care.

Coverage and Reimbursement Schemes for Behavioral Therapy

Although intensive lifestyle behavior therapy has been identified as a key strategy for addressing the rise in cardiovascular and other preventable chronic disease,7 several barriers, including cost and access, have historically kept many from benefiting from this evidence-based care. Recent health system reforms have been designed to help remove these barriers. The goal of the Affordable Care Act (ACA), passed by the US Congress in 2010, is to improve health care access and delivery while controlling related costs. The following sections briefly describe provisions of the ACA designed to help achieve these goals.55

Promotion of Evidence-Based Prevention

The ACA requires that health policies (public and privately funded) cover, at no cost to patients, preventive services for which there is strong evidence of health benefits as determined by the US Preventive Services Task Force. This includes, for example, intensive, multicomponent counseling and behavioral interventions to promote sustained weight loss for patients with obesity.56 To be reimbursable, this counseling must meet the following criteria:

  • Include the following elements:

    • – Behavioral management

    • – Improving diet/nutrition and increasing PA

    • – Addressing barriers to change

    • – Self-monitoring

    • – Strategies for maintenance

  • Use the US Preventive Services Task Force–recommended 5A counseling framework (assess, advise, agree, assist, and arrange)57

  • Be provided by primary care physicians or other health care professionals (eg, nurse practitioner, clinical nurse specialist, physician assistant, or registered dietitians) performing within statutory scopes of practice and practice authority

  • Include 12 to 26 individual or group sessions each year according to an established schedule and offer eligibility for additional face-to-face visits contingent on weight loss progress

Strengthening Primary Health Care

Based on evidence that comprehensive, coordinated, and well-targeted primary care can improve outcomes and reduce per-patient costs,58,59 the ACA includes strategies designed to strengthen the primary care system. This includes the payment of financial incentives to primary health care professionals who participate in the Centers for Medicare & Medicaid Services program and promotion of the patient-centered medical home care models by offering states the option to increase reimbursement to primary care sites designated as health homes for Medicaid patients with chronic conditions. The patient-centered medical home model emphasizes the following:

  • Enhanced patient access to a regular source of primary care

  • Stable and ongoing relationships with a personal clinician who directs a care team

  • Timely, well-organized health services that emphasize prevention and long-term care management.55

The reforms of the ACA also seek to strengthen primary care by facilitating research into ways to improve the quality of care provided, sharing promising models, and integrating primary care more seamlessly with other health care services such as behavioral health and long-term care.59

Shift to an Accountable Care Organization Model

Accountable care organizations are networks of doctors, hospitals, and other health care professionals who volunteer to work together to take financial and medical responsibility for a group of patients,60 with a goal of shifting the financial incentives from greater volume to better outcomes through better coordination of care.61 The Shared Savings Program of the Centers for Medicare & Medicaid Services provides financial incentive for the creation of accountable care organizations.62 Those that meet quality benchmarks and keep spending below budget receive half the subsequent savings. Research shows that cost-saving is achievable while improving care quality.63

Expansion of Telehealth Services

Technological advances over recent decades have increased the potential for telehealth to improve the reach and quality of health services delivery in a cost-effective way. Incentives created through the ACA led to an expansion in the use of telehealth through the Medicare and Medicaid programs,64 and currently, most states require that private insurers reimburse health care professionals for telehealth services.

Barriers to Adoption, Ongoing Gaps, and Calls for Future Research

As noted, several strategies have been developed to enhance the feasibility of delivering effective behavioral counseling interventions in primary care to influence patient behavior change and to provide support to maintain change through coordinated care. However, the inclusion of primary care–feasible behavioral counseling intervention trials that were conducted outside the United States may limit generalizability to health practice systems operating in the United States or in other countries. In addition, broadscale adoption of evidence-based interventions within health care systems is not practical and incurs administrative constraints, including time, workflow, and limited resources. Policy, law, or system-level regulatory factors further perpetuate barriers to primary care professionals to coordinate comprehensive behavioral counseling and follow-up care for their patients, including referral methods with clinical communities. An effective referral system is highly predicated on the successful coordination of delivery of care and collaborations between health professionals and clinical-community settings. Despite this, current challenges in integrating effective referral schemes stem from limited availability of or inadequately developed coordinated care models or limited awareness of evidence-based behavioral counseling resources within the community.26 Consequently, these factors have hindered the translation of evidence-based behavior counseling interventions in clinic-community–linked settings, particularly those serving underrepresented and under-resourced populations (eg, those residing in rural areas). 65 Developing and fostering sustainable clinic-community links through referral systems are integral to ensuring access to and availability of effective, equitable patient-centered preventive care. These partnerships can also maximize patient engagement by assisting with health behavior change and arranging follow-up care on the basis of the patient’s progress and preferences as needed (Figure).


Figure. Health care professional workflow for adoption and implementation of behavior change interventions in primary care and community-based settings. Given the constraints experienced with busy, infrequent clinic visits, this gives primary health care professionals a road map to help provide effective behavioral intervention programs in primary care using primary care professional–directed referrals to other health care professionals and access to clinical and community resources according to patient preferences and risk behaviors. PA indicates physical activity.

One potential clinic-community link is federally qualified health centers and rural health clinics, which make up the largest primary care network in the United States and provide comprehensive care to diverse and underserved populations. However, these clinics face several unique barriers to adopting behavioral intervention programs. In a program evaluation brief on self-measured blood pressure monitoring implemented in 5 federally qualified health centers in Hawaii,30 technological and equipment limitations, participant transient status resulting in lack of follow-up and loss of equipment, staff turnover attributable to loss of grant funding, lack of a standard curriculum, and data management time burdens were all barriers to implementation. Previous focus groups have identified that reimbursement for health counseling, health care professional burnout, lack of patient knowledge and adherence, and socioeconomic factors, including poor health literacy, were prominent issues.31 Similar barriers have also been reported in weight management and PA interventions, as well as a lack of interpreters and transportation services, which is likely to disproportionately affect those living in rural areas. Additional programmatic barriers contribute to inadequate access to resources and materials, which limits recruitment, scalability, and sustainability of behavior counseling interventions. Loss and turnover of staff compound referral backlogs and may require that health care professionals be cross-trained across programs.32 Therefore, further investigation is needed to evaluate the reach and effectiveness of behavior counseling intervention models, including those with a strong evidence base, in promoting meaningful, long-lasting change in cardiovascular health behaviors across diverse and medically marginalized populations.

Insufficient or absent reimbursement is a burdensome financial barrier faced by health care professionals that further impedes effective adoption and implementation of behavior counseling in primary care practice. Cumbersome regulation of reimbursement such as strict documentation of counseling prescribed and lack of financial incentive for these services33 hinder uptake of these crucial services. For obesity counseling specifically, intensive behavior counseling is reimbursed only when provided to patients with a body mass index of ≥30 kg/m2 and delivered on site by higher-level primary care professionals (physicians, nurse practitioners, or physician assistants), whereas services provided outside of a physical office visit such as by telephone or in the community are excluded.34,35 Although the Centers for Medicare & Medicaid Services covers face-to-face counseling with the health care professional, visits are brief (10–15 minutes), delivered at a lower intensity than empirically tested behavior counseling interventions, and capped at a maximum of 22 visits over 6 months, with the option to cover additional once-a-month visits for an additional 6 months contingent on whether the patient achieved a weight loss of 3 kg during the course of the first 6 months of counseling. These regulations worsen health disparities and compound problems in the already fragmented preventive care system in the United States. For instance, nonresponders to lower-intensity counseling have more difficulty meeting criteria to maintain continuity of care, and their health care professionals are limited in their ability to assist and arrange intensive follow-up care necessary to maintain long-term behavior change progress.

However, with the dawn of different reimbursement models such as value-based care and accountable care organizations, an opportunity exists to build the financial model for healthy lifestyle teams.36 The team of health professionals, including physicians, nurses and nurse practitioners, exercise physiologists, registered dieticians, behavioral counselors, and others as needed, addresses the lifestyle problems that lead to noncommunicable diseases, including CVD. As previously noted, a fundamental barrier in reimbursement is the misalignment of factors that contribute to health outcomes and services reimbursed.36 According to the National Academies of Sciences, Engineering, and Medicine 2019 report,37 social care is one of the major factors that contribute to health outcomes. Primary challenges to integrating social and health care include payment reform. Although payment reform has moved away from fee-for-service and toward value-based payment, it is necessary to state and acknowledge social care activities, expand on which individuals can bill for such services, and determine how accountable care models with and without integration affect health.

Addressing knowledge gaps will require greater investments in scientific and implementation research to identify best-practice approaches (team-based care, referral, and reimbursement models) to improve the feasibility, integration, and broadscale delivery of behavior counseling within clinical and community settings. It is important to note that this scientific statement included primary care–feasible randomized clinical trials published from 2005 to 2020. However, as the evidence base for primary care–feasible models of behavioral counseling interventions continues to advance, larger-scale studies of behavioral counseling interventions that effectively improve CVD risk behaviors are needed to determine the feasibility of adoption and implementation in health systems. Future studies addressing innovative approaches to maximize the retention of participants in programs for ≥1 year are needed to evaluate intensity, treatment receptivity, and effectiveness of health care professional–delivered behavior counseling interventions on the maintenance of behavioral outcomes across diverse middle-aged and older adult populations with CVD risk factors. In addition, future investigative efforts are encouraged to identify effective approaches that promote health equity in the delivery of lifestyle behavior counseling interventions in clinical or community settings that serve underrepresented and low-socioeconomic-status patient populations. A focus on approaches to improve health equity among high-risk patient populations is consistent with the American Heart Association 2024 Health Equity Impact Goals and is critical for effectively reducing CVD disparities. Strengthening collaborations among the American Heart Association, policymakers, private stakeholders, and national and community public health agencies will be imperative to facilitate more immediate and actionable plans that address system-level barriers to providing equitable prevention services, including behavior counseling interventions in clinic-community–linked practices, and to promote long-lasting changes in cardiovascular health behaviors across all populations that contribute to meeting national targets for CVD prevention.


This scientific statement describes the feasibility for health care professionals to offer or refer effective, multicomponent, evidence-based behavior counseling interventions in primary care settings to promote healthy behaviors and to reduce CVD risk in middle-aged and older adults. This scientific statement additionally presents an overview of equitable resources, including national and local implementation of CVD risk reduction/management programs, that facilitate clinic-community partnerships and the practical integration of patient-centered behavior counseling within diverse primary care and community settings. Primary health care professionals are viewed as the gatekeepers to delivering intensive behavior counseling to at-risk patients, with consistent evidence showing that healthcare professional–facilitated behavior counseling improves cardiovascular risk behaviors and reduces CVD outcomes in adults with known CVD risk factors. Assisting patients in achieving health behavior goals and arranging follow-up support—critical tenets of the 5A Model for health behavior counseling in primary care—are especially important to produce meaningful and lasting behavior change. However, these steps are delivered the least often by primary care professionals. This scientific advisory statement is intended to enhance health care professional efforts to adopt or implement comprehensive, evidence-based behavior counseling interventions in primary care settings. In particular, the scientific statement discusses approaches beyond what can be performed during brief, episodic office visits by encouraging the use of team-based care, reimbursement and referral models, and other best-practice approaches to promote patient progress in maintaining healthy behavior change for primary CVD prevention. Supporting health care professionals with guidance on how to feasibly deliver or refer effective behavior counseling is a critical facet of improving the provision of primary prevention that is needed to reduce the burden of CVD in the growing aging population.

Article Information


The American Heart Association makes every effort to avoid any actual or potential conflicts of interest that may arise as a result of an outside relationship or a personal, professional, or business interest of a member of the writing panel. Specifically, all members of the writing group are required to complete and submit a Disclosure Questionnaire showing all such relationships that might be perceived as real or potential conflicts of interest.

This statement was approved by the American Heart Association Science Advisory and Coordinating Committee on May 17, 2021, and the American Heart Association Executive Committee on June 21, 2021. A copy of the document is available at by using either “Search for Guidelines & Statements” or the “Browse by Topic” area. To purchase additional reprints, call 215-356-2721 or email

The American Heart Association requests that this document be cited as follows: Laddu D, Ma J, Kaar J, Ozemek C, Durant RW, Campbell T, Welsh J, Turrise S; on behalf of the American Heart Association Behavioral Change for Improving Health Factors Committee of the Council on Epidemiology and Prevention and the Council on Lifestyle and Cardiometabolic Health; Council on Arteriosclerosis, Thrombosis and Vascular Biology; Council on Hypertension; and Stroke Council. Health behavior change programs in primary care and community practices for cardiovascular disease prevention and risk factor management among midlife and older adults: a scientific statement from the American Heart Association. Circulation. 2021;144:e533–e549. doi: 10.1161/CIR.0000000000001026

The expert peer review of AHA-commissioned documents (eg, scientific statements, clinical practice guidelines, systematic reviews) is conducted by the AHA Office of Science Operations. For more on AHA statements and guidelines development, visit Select the “Guidelines & Statements” drop-down menu, then click “Publication Development.”

Permissions: Multiple copies, modification, alteration, enhancement, and/or distribution of this document are not permitted without the express permission of the American Heart Association. Instructions for obtaining permission are located at A link to the “Copyright Permissions Request Form” appears in the second paragraph (


  • 1. Virani SS, Alonso A, Benjamin EJ, Bittencourt MS, Callaway CW, Carson AP, Chamberlain AM, Chang AR, Cheng S, Delling FNet al; on behalf of the American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee. Heart disease and stroke statistics–2020 update: a report from the American Heart Association.Circulation. 2020; 141:e139–e596. doi: 10.1161/CIR.0000000000000757LinkGoogle Scholar
  • 2. Centers for Disease Control and Prevention. Vital signs: avoidable deaths from heart disease, stroke, and hypertensive disease–United States, 2001–2010.MMWR Morb Mortal Wkly Rep. 2013; 62:721–727.MedlineGoogle Scholar
  • 3. Yang Q, Cogswell ME, Flanders WD, Hong Y, Zhang Z, Loustalot F, Gillespie C, Merritt R, Hu FB. Trends in cardiovascular health metrics and associations with all-cause and CVD mortality among US adults.JAMA. 2012; 307:1273–1283. doi: 10.1001/jama.2012.339CrossrefMedlineGoogle Scholar
  • 4. Arnett DK, Blumenthal RS, Albert MA, Buroker AB, Goldberger ZD, Hahn EJ, Himmelfarb CD, Khera A, Lloyd-Jones D, McEvoy JW, et al. 2019 ACC/AHA guideline on the primary prevention of cardiovascular disease: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines [published corrections appear in Circulation. 2019;140:e649–e650; Circulation. 2020;141:e60; Circulation. 2020;141:e774].Circulation. 2019; 140:e596–e646. doi: 10.1161/CIR.0000000000000678LinkGoogle Scholar
  • 5. Eckel RH, Jakicic JM, Ard JD, de Jesus JM, Houston Miller N, Hubbard VS, Lee IM, Lichtenstein AH, Loria CM, Millen BE, et al. 2013 AHA/ACC guideline on lifestyle management to reduce cardiovascular risk: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines [published corrections appear in Circulation. 2014;129:S100–S101; Circulation. 2015;131:e326].Circulation. 2014; 129(25 suppl 2):S76–S99. doi: 10.1161/01.cir.0000437740.48606.d1LinkGoogle Scholar
  • 6. Physical Activity Guidelines Advisory Committee. 2018 Physical Activity Guidelines Advisory Committee Scientific Report. Department of Health and Human Services; 2018.Google Scholar
  • 7. LeFevre ML; U.S. Preventive Services Task Force. Behavioral counseling to promote a healthful diet and physical activity for cardiovascular disease prevention in adults with cardiovascular risk factors: U.S. Preventive Services Task Force Recommendation Statement.Ann Intern Med. 2014; 161:587–593. doi: 10.7326/M14-1796CrossrefMedlineGoogle Scholar
  • 8. Barghi A, Torres H, Kressin NR, McCormick D. Coverage and access for Americans with cardiovascular disease or risk factors after the ACA: a quasi-experimental study.J Gen Intern Med. 2019; 34:1797–1805. doi: 10.1007/s11606-019-05108-1CrossrefMedlineGoogle Scholar
  • 9. Grossman DC, Bibbins-Domingo K, Curry SJ, Barry MJ, Davidson KW, Doubeni CA, Epling JW, Kemper AR, Krist AH, Kurth AE, et al. Behavioral counseling to promote a healthful diet and physical activity for cardiovascular disease prevention in adults without cardiovascular risk factors: US Preventive Services Task Force recommendation statement.JAMA. 2017; 318:167–174. doi: 10.1001/jama.2017.7171CrossrefMedlineGoogle Scholar
  • 10. Bowen DJ, Beresford SA. Dietary interventions to prevent disease.Annu Rev Public Health. 2002; 23:255–286. doi: 10.1146/annurev.publhealth.23.100901.140555CrossrefMedlineGoogle Scholar
  • 11. Doménech M, Roman P, Lapetra J, García de la Corte FJ, Sala-Vila A, de la Torre R, Corella D, Salas-Salvadó J, Ruiz-Gutiérrez V, Lamuela-Raventós RM, et al. Mediterranean diet reduces 24-hour ambulatory blood pressure, blood glucose, and lipids: one-year randomized, clinical trial.Hypertension. 2014; 64:69–76. doi: 10.1161/HYPERTENSIONAHA.113.03353LinkGoogle Scholar
  • 12. Salas-Salvadó J, Díaz-López A, Ruiz-Canela M, Basora J, Fitó M, Corella D, Serra-Majem L, Wärnberg J, Romaguera D, Estruch R, et al; PREDIMED-Plus Investigators. Effect of a lifestyle intervention program with energy-restricted Mediterranean diet and exercise on weight loss and cardiovascular risk factors: one-year results of the PREDIMED-Plus trial.Diabetes Care. 2019; 42:777–788. doi: 10.2337/dc18-0836CrossrefMedlineGoogle Scholar
  • 13. Steinberg D, Kay M, Burroughs J, Svetkey LP, Bennett GG. The effect of a digital behavioral weight loss intervention on adherence to the Dietary Approaches to Stop Hypertension (DASH) dietary pattern in medically vulnerable primary care patients: results from a randomized controlled trial.J Acad Nutr Diet. 2019; 119:574–584. doi: 10.1016/j.jand.2018.12.011CrossrefMedlineGoogle Scholar
  • 14. Sacerdote C, Fiorini L, Rosato R, Audenino M, Valpreda M, Vineis P. Randomized controlled trial: effect of nutritional counselling in general practice.Int J Epidemiol. 2006; 35:409–415. doi: 10.1093/ije/dyi170CrossrefMedlineGoogle Scholar
  • 15. Fries E, Edinboro P, McClish D, Manion L, Bowen D, Beresford SA, Ripley J. Randomized trial of a low-intensity dietary intervention in rural residents: the Rural Physician Cancer Prevention Project.Am J Prev Med. 2005; 28:162–168. doi: 10.1016/j.amepre.2004.10.017CrossrefMedlineGoogle Scholar
  • 16. US Department of Agriculture and US Department of Health and Human Services. Dietary Guidelines for Americans, 2020–2025.Accessed February 23, 2021. https://dietaryguidelines.govGoogle Scholar
  • 17. Czajkowski SM, Powell LH, Adler N, Naar-King S, Reynolds KD, Hunter CM, Laraia B, Olster DH, Perna FM, Peterson JC, et al. From ideas to efficacy: the ORBIT model for developing behavioral treatments for chronic diseases.Health Psychol. 2015; 34:971–982. doi: 10.1037/hea0000161CrossrefMedlineGoogle Scholar
  • 18. Sallis RE, Baggish AL, Franklin BA, Whitehead JR. The call for a physical activity vital sign in clinical practice.Am J Med. 2016; 129:903–905. doi: 10.1016/j.amjmed.2016.05.005CrossrefMedlineGoogle Scholar
  • 19. Johnson ST, Mundt C, Qiu W, Soprovich A, Wozniak L, Plotnikoff RC, Johnson JA. Increase in daily steps after an exercise specialist led lifestyle intervention for adults with type 2 diabetes in primary care: a controlled implementation trial.J Phys Act Health. 2015; 12:1492–1499. doi: 10.1123/jpah.2014-0200CrossrefMedlineGoogle Scholar
  • 20. Harris T, Kerry SM, Limb ES, Victor CR, Iliffe S, Ussher M, Whincup PH, Ekelund U, Fox-Rushby J, Furness C, et al. Effect of a primary care walking intervention with and without nurse support on physical activity levels in 45- to 75-year-olds: the Pedometer And Consultation Evaluation (PACE-UP) Cluster Randomised Clinical Trial.PLoS Med. 2017; 14:e1002210. doi: 10.1371/journal.pmed.1002210CrossrefMedlineGoogle Scholar
  • 21. Pinto BM, Goldstein MG, Ashba J, Sciamanna CN, Jette A. Randomized controlled trial of physical activity counseling for older primary care patients.Am J Prev Med. 2005; 29:247–255. doi: 10.1016/j.amepre.2005.06.016CrossrefMedlineGoogle Scholar
  • 22. Petrella RJ, Lattanzio CN, Shapiro S, Overend T. Improving aerobic fitness in older adults: effects of a physician-based exercise counseling and prescription program.Can Fam Physician. 2010; 56:e191–e200.MedlineGoogle Scholar
  • 23. Coleman KJ, Farrell MA, Rocha DA, Hayashi T, Hernandez M, Wolf J, Lindsay S. Readiness to be physically active and self-reported physical activity in low-income Latinas, California WISEWOMAN, 2006-2007.Prev Chronic Dis. 2012; 9:E87.MedlineGoogle Scholar
  • 24. Grandes G, Sanchez A, Sanchez-Pinilla RO, Torcal J, Montoya I, Lizarraga K, Serra J; PEPAF Group. Effectiveness of physical activity advice and prescription by physicians in routine primary care: a cluster randomized trial.Arch Intern Med. 2009; 169:694–701. doi: 10.1001/archinternmed.2009.23CrossrefMedlineGoogle Scholar
  • 25. Writing Group for the Activity Counseling Trial Research Group. Effects of physical activity counseling in primary care: the Activity Counseling Trial: a randomized controlled trial.JAMA. 2001; 286:677–687. doi: 10.1001/jama.286.6.677CrossrefMedlineGoogle Scholar
  • 26. Carroll JK, Lewis BA, Marcus BH, Lehman EB, Shaffer ML, Sciamanna CN. Computerized tailored physical activity reports: a randomized controlled trial.Am J Prev Med. 2010; 39:148–156. doi: 10.1016/j.amepre.2010.04.005CrossrefMedlineGoogle Scholar
  • 27. Kerse N, Elley CR, Robinson E, Arroll B. Is physical activity counseling effective for older people? A cluster randomized, controlled trial in primary care.J Am Geriatr Soc. 2005; 53:1951–1956. doi: 10.1111/j.1532-5415.2005.00466.xCrossrefMedlineGoogle Scholar
  • 28. Christian JG, Bessesen DH, Byers TE, Christian KK, Goldstein MG, Bock BC. Clinic-based support to help overweight patients with type 2 diabetes increase physical activity and lose weight.Arch Intern Med. 2008; 168:141–146. doi: 10.1001/archinternmed.2007.13CrossrefMedlineGoogle Scholar
  • 29. Vadheim LM, Patch K, Brokaw SM, Carpenedo D, Butcher MK, Helgerson SD, Harwell TS. Telehealth delivery of the diabetes prevention program to rural communities.Transl Behav Med. 2017; 7:286–291. doi: 10.1007/s13142-017-0496-yCrossrefMedlineGoogle Scholar
  • 30. Ma J, Yank V, Xiao L, Lavori PW, Wilson SR, Rosas LG, Stafford RS. Translating the Diabetes Prevention Program lifestyle intervention for weight loss into primary care: a randomized trial.JAMA Intern Med. 2013; 173:113–121. doi: 10.1001/2013.jamainternmed.987CrossrefMedlineGoogle Scholar
  • 31. Bennett GG, Warner ET, Glasgow RE, Askew S, Goldman J, Ritzwoller DP, Emmons KM, Rosner BA, Colditz GA; Be Fit, Be Well Study Investigators. Obesity treatment for socioeconomically disadvantaged patients in primary care practice.Arch Intern Med. 2012; 172:565–574. doi: 10.1001/archinternmed.2012.1CrossrefMedlineGoogle Scholar
  • 32. Nolan RP, Feldman R, Dawes M, Kaczorowski J, Lynn H, Barr SI, MacPhail C, Thomas S, Goodman J, Eysenbach G, et al. Randomized controlled trial of e-counseling for hypertension: REACH.Circ Cardiovasc Qual Outcomes. 2018; 11:e004420. doi: 10.1161/CIRCOUTCOMES.117.004420LinkGoogle Scholar
  • 33. Bennett GG, Steinberg D, Askew S, Levine E, Foley P, Batch BC, Svetkey LP, Bosworth HB, Puleo EM, Brewer A, et al. Effectiveness of an App and provider counseling for obesity treatment in primary care.Am J Prev Med. 2018; 55:777–786. doi: 10.1016/j.amepre.2018.07.005CrossrefMedlineGoogle Scholar
  • 34. Appel LJ, Clark JM, Yeh HC, Wang NY, Coughlin JW, Daumit G, Miller ER, Dalcin A, Jerome GJ, Geller S, et al. Comparative effectiveness of weight-loss interventions in clinical practice.N Engl J Med. 2011; 365:1959–1968. doi: 10.1056/NEJMoa1108660CrossrefMedlineGoogle Scholar
  • 35. Wadden TA, Volger S, Sarwer DB, Vetter ML, Tsai AG, Berkowitz RI, Kumanyika S, Schmitz KH, Diewald LK, Barg R, et al. A two-year randomized trial of obesity treatment in primary care practice.N Engl J Med. 2011; 365:1969–1979. doi: 10.1056/NEJMoa1109220CrossrefMedlineGoogle Scholar
  • 36. Burke V, Beilin LJ, Cutt HE, Mansour J, Williams A, Mori TA. A lifestyle program for treated hypertensives improved health-related behaviors and cardiovascular risk factors, a randomized controlled trial.J Clin Epidemiol. 2007; 60:133–141. doi: 10.1016/j.jclinepi.2006.05.012CrossrefMedlineGoogle Scholar
  • 37. Elmer PJ, Obarzanek E, Vollmer WM, Simons-Morton D, Stevens VJ, Young DR, Lin PH, Champagne C, Harsha DW, Svetkey LP, et al; PREMIER Collaborative Research Group. Effects of comprehensive lifestyle modification on diet, weight, physical fitness, and blood pressure control: 18-month results of a randomized trial.Ann Intern Med. 2006; 144:485–495. doi: 10.7326/0003-4819-144-7-200604040-00007CrossrefMedlineGoogle Scholar
  • 38. Svetkey LP, Pollak KI, Yancy WS, Dolor RJ, Batch BC, Samsa G, Matchar DB, Lin PH. Hypertension improvement project: randomized trial of quality improvement for physicians and lifestyle modification for patients.Hypertension. 2009; 54:1226–1233. doi: 10.1161/HYPERTENSIONAHA.109.134874LinkGoogle Scholar
  • 39. Martin PD, Dutton GR, Rhode PC, Horswell RL, Ryan DH, Brantley PJ. Weight loss maintenance following a primary care intervention for low-income minority women.Obesity (Silver Spring). 2008; 16:2462–2467. doi: 10.1038/oby.2008.399CrossrefMedlineGoogle Scholar
  • 40. Parra-Medina D, Wilcox S, Salinas J, Addy C, Fore E, Poston M, Wilson DK. Results of the Heart Healthy and Ethnically Relevant Lifestyle trial: a cardiovascular risk reduction intervention for African American women attending community health centers.Am J Public Health. 2011; 101:1914–1921. doi: 10.2105/AJPH.2011.300151CrossrefMedlineGoogle Scholar
  • 41. Kumanyika SK, Shults J, Fassbender J, Whitt MC, Brake V, Kallan MJ, Iqbal N, Bowman MA. Outpatient weight management in African-Americans: the Healthy Eating and Lifestyle Program (HELP) study.Prev Med. 2005; 41:488–502. doi: 10.1016/j.ypmed.2004.09.049CrossrefMedlineGoogle Scholar
  • 42. Edelman D, Oddone EZ, Liebowitz RS, Yancy WS, Olsen MK, Jeffreys AS, Moon SD, Harris AC, Smith LL, Quillian-Wolever RE, et al. A multidimensional integrative medicine intervention to improve cardiovascular risk.J Gen Intern Med. 2006; 21:728–734. doi: 10.1111/j.1525-1497.2006.00495.xCrossrefMedlineGoogle Scholar
  • 43. Sanchez A, Bully P, Martinez C, Grandes G. Effectiveness of physical activity promotion interventions in primary care: a review of reviews.Prev Med. 2015; 76(suppl):S56–S67. doi: 10.1016/j.ypmed.2014.09.012CrossrefMedlineGoogle Scholar
  • 44. Jensen MD, Ryan DH, Apovian CM, Ard JD, Comuzzie AG, Donato KA, Hu FB, Hubbard VS, Jakicic JM, Kushner RF, et al. 2013 AHA/ACC/TOS guideline for the management of overweight and obesity in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and The Obesity Society [published correction appears in Circulation. 2014;129:S139–S140].Circulation. 2014; 129(25 suppl 2):S102–S138. doi: 10.1161/01.cir.0000437739.71477.eeLinkGoogle Scholar
  • 45. Ferdinand KC, Patterson KP, Taylor C, Fergus IV, Nasser SA, Ferdinand DP. Community-based approaches to prevention and management of hypertension and cardiovascular disease.J Clin Hypertens (Greenwich). 2012; 14:336–343. doi: 10.1111/j.1751-7176.2012.00622.xCrossrefMedlineGoogle Scholar
  • 46. Reynolds J, Thibodeaux L, Jiang L, Francis K, Hochhalter A. Fit & Strong! promotes physical activity and well-being in older cancer survivors.Front Public Health. 2014; 2:171. doi: 10.3389/fpubh.2014.00171CrossrefMedlineGoogle Scholar
  • 47. Jasik CB, Joy E, Brunisholz KD, Kirley K. Practical tips for implementing the diabetes prevention program in clinical practice.Curr Diab Rep. 2018; 18:70. doi: 10.1007/s11892-018-1034-0CrossrefMedlineGoogle Scholar
  • 48. Centers for Disease Control and Prevention. National Diabetes Prevention Program.Accessed November 16, 2020. Scholar
  • 49. YMCA. YMCA Diabetes Prevention Program.Accessed February 22, 2021. Scholar
  • 50. Stewart EE, Taylor-Post N, Nichols L, Staton EW, Schleunning A. Community connections linking primary care patients to local resources for better management of obesity.2014. Accessed February 22, 2021. Scholar
  • 51. Community Preventive Services Task Force. Community guide: cardiovascular disease.Accessed February 22, 2021. Scholar
  • 52. Lloyd-Jones DM, Huffman MD, Karmali KN, Sanghavi DM, Wright JS, Pelser C, Gulati M, Masoudi FA, Goff DC. Estimating longitudinal risks and benefits from cardiovascular preventive therapies among Medicare patients: the Million Hearts Longitudinal ASCVD Risk Assessment Tool: a special report from the American Heart Association and American College of Cardiology.Circulation. 2017; 135:e793–e813. doi: 10.1161/CIR.0000000000000467LinkGoogle Scholar
  • 53. Morgan JM, Mensa-Wilmot Y, Bowen SA, Murphy M, Bonner T, Rutledge S, Rutledge G. Implementing key drivers for diabetes self-management education and support programs: early outcomes, activities, facilitators, and barriers.Prev Chronic Dis. 2018; 15:E15. doi: 10.5888/pcd15.170399CrossrefMedlineGoogle Scholar
  • 54. Covert H, Sherman M, Miner K, Lichtveld M. Core competencies and a workforce framework for community health workers: a model for advancing the profession.Am J Public Health. 2019; 109:320–327. doi: 10.2105/AJPH.2018.304737CrossrefMedlineGoogle Scholar
  • 55. Davis K, Abrams M, Stremikis K. How the Affordable Care Act will strengthen the nation’s primary care foundation.J Gen Intern Med. 2011; 26:1201–1203. doi: 10.1007/s11606-011-1720-yCrossrefMedlineGoogle Scholar
  • 56. Centers for Medicare & Medicaid Services. Decision memo for intensive behavioral therapy for obesity (CAG-00423N).Accessed October 15, 2020. Scholar
  • 57. Whitlock EP, Orleans CT, Pender N, Allan J. Evaluating primary care behavioral counseling interventions: an evidence-based approach.Am J Prev Med. 2002; 22:267–284. doi: 10.1016/s0749-3797(02)00415-4CrossrefMedlineGoogle Scholar
  • 58. Shi L. The impact of primary care: a focused review.Scientifica (Cairo). 2012; 2012:432892. doi: 10.6064/2012/432892CrossrefMedlineGoogle Scholar
  • 59. Abrams MK, Nuzum R, Zezza MA, Ryan J, Kiszla J, Guterman S. The Affordable Care Act’s payment and delivery system reforms: a progress report at five years.May 2015. Accessed November 12, 2020. Scholar
  • 60. Rittenhouse DR, Shortell SM, Fisher ES. Primary care and accountable care: two essential elements of delivery-system reform.N Engl J Med. 2009; 361:2301–2303. doi: 10.1056/NEJMp0909327CrossrefMedlineGoogle Scholar
  • 61. Fisher ESShortell SMKreindler SAVan Citters ADLarson BK. A framework for evaluating the formation, implementation, and performance of accountable care organizations.Health Aff (Millwood). 2012; 31:2368–2378. doi: 10.1377/hlthaff.2012.0544CrossrefMedlineGoogle Scholar
  • 62. LeVine AM, Whitsett JA, Gwozdz JA, Richardson TR, Fisher JH, Burhans MS, Korfhagen TR. Distinct effects of surfactant protein A or D deficiency during bacterial infection on the lung.J Immunol. 2000; 165:3934–3940. doi: 10.4049/jimmunol.165.7.3934CrossrefMedlineGoogle Scholar
  • 63. Adler DG. Yamada’s Textbook of Gastroenterology.Gastroenterology. 2017; 152:667–668. doi: Scholar
  • 64. Elliott VL. Telehealth and telemedicine: description and issues.Accessed November 24, 2020. Scholar
  • 65. Ahmed NU, Delgado M, Saxena A. Trends and disparities in the prevalence of physicians’ counseling on diet and nutrition among the U.S. adult population, 2000-2011.Prev Med. 2016; 89:70–75. doi: 10.1016/j.ypmed.2016.05.014CrossrefMedlineGoogle Scholar


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