AHA Scientific Statement

Interventions to Promote Physical Activity and DietaryLifestyle Changes for Cardiovascular Risk Factor Reduction

in AdultsA Scientific Statement From the American Heart Association

Endorsed by the Preventive Cardiovascular Nurses Association and the Society ofBehavioral Medicine

Nancy T. Artinian, PhD, RN, FAHA, Chair; Gerald F. Fletcher, MD, FAHA, Co-Chair;Dariush Mozaffarian, MD, DrPH, FAHA; Penny Kris-Etherton, PhD, RD, FAHA;

Linda Van Horn, PhD, RD, FAHA; Alice H. Lichtenstein, DSc, FAHA;Shiriki Kumanyika, PhD, MPH, FAHA; William E. Kraus, MD, FAHA; Jerome L. Fleg, MD, FAHA;

Nancy S. Redeker, PhD, RN, FAHA; Janet C. Meininger, PhD, RN; JoAnne Banks, RN, PhD;Eileen M. Stuart-Shor, PhD, ANP, FAHA; Barbara J. Fletcher, RN, MN, FAHA;

Todd D. Miller, MD, FAHA; Suzanne Hughes, MSN, RN, FAHA; Lynne T. Braun, PhD, CNP, FAHA;Laurie A. Kopin, MS, RN, ANP, FPCNA; Kathy Berra, MSN, ANP, FAHA;

Laura L. Hayman, PhD, RN, FAHA; Linda J. Ewing, PhD, RN; Philip A. Ades, MD;J. Larry Durstine, PhD; Nancy Houston-Miller, BSN, FAHA;

Lora E. Burke, PhD, MPH, FAHA, Steering Committee Co-Chair; on behalf of the American HeartAssociation Prevention Committee of the Council on Cardiovascular Nursing

Approximately 79 400 000 American adults, or 1 in 3, havecardiovascular disease (CVD).1 CVD accounts for 36.3%

or 1 of every 2.8 deaths in the United States and is the leadingcause of death among both men and women in the United States,killing an average of 1 American every 37 seconds.1 Olderadults, some ethnic minority populations, and socioeconomicallydisadvantaged individuals have an increased prevalence of CVDand vascular/metabolic risk factors such as hypertension, dys-lipidemia, and diabetes; are more likely to have �2 risk factors;and are at increased risk of being sedentary, overweight orobese, and having unhealthy dietary habits.2–10 Black and His-panic immigrants are initially at lower risk for vascular/metabolicrisk factors and CVD than US-born black and Hispanic individu-als,2 but as they adapt to the diet and activity habits of this country,

the prevalence of vascular/metabolic risk factors increases.3 Each ofthese issues emphasizes the importance of interventions to promotephysical activity (PA) and healthy diets in all American adults.

Even modest sustained lifestyle changes can substantiallyreduce CVD morbidity and mortality. Because many of thebeneficial effects of lifestyle changes accrue over time,long-term adherence maximizes individual and populationbenefits. Interventions targeting dietary patterns, weight re-duction, and new PA habits often result in impressive rates ofinitial behavior changes, but frequently are not translated intolong-term behavioral maintenance.4 Both adoption and main-tenance of new cardiovascular risk-reducing behaviors posechallenges for many individuals. According to the NationalCenter for Health Statistics, life expectancy could increase by

The American Heart Association makes every effort to avoid any actual or potential conflicts of interest that may arise as a result of an outsiderelationship or a personal, professional, or business interest of a member of the writing panel. Specifically, all members of the writing group are requiredto 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 4, 2010. A copy of thestatement is available at http://www.americanheart.org/presenter.jhtml?identifier�3003999 by selecting either the “topic list” link or the “chronologicallist” link (No. KB-0043). To purchase additional reprints, call 843-216-2533 or e-mail kelle.ramsay@wolterskluwer.com.

The American Heart Association requests that this document be cited as follows: Artinian NT, Fletcher GF, Mozaffarian D, Kris-Etherton P, Van HornL, Lichtenstein AH, Kumanyika S, Kraus WE, Fleg JL, Redeker NS, Meininger JC, Banks J, Stuart-Shor EM, Fletcher BJ, Miller TD, Hughes S, BraunLT, Kopin LA, Berra K, Hayman LL, Ewing LJ, Ades PA, Durstine L, Houston-Miller N, Burke LE; on behalf of the American Heart AssociationPrevention Committee of the Council on Cardiovascular Nursing. Interventions to promote physical activity and dietary lifestyle changes forcardiovascular risk factor reduction in adults: a scientific statement from the American Heart Association. Circulation. 2010;122:406–441.

Expert peer review of AHA Scientific Statements is conducted at the AHA National Center. For more on AHA statements and guidelines development,visit http://www.americanheart.org/presenter.jhtml?identifier�3023366.

Permissions: Multiple copies, modification, alteration, enhancement, and/or distribution of this document are not permitted without the expresspermission of the American Heart Association. Instructions for obtaining permission are located at http://www.americanheart.org/presenter.jhtml?identifier�4431. A link to the “Permission Request Form” appears on the right side of the page.

(Circulation. 2010;122:406-441.)© 2010 American Heart Association, Inc.

Circulation is available at http://circ.ahajournals.org DOI: 10.1161/CIR.0b013e3181e8edf1

406

almost 7 years if all forms of major CVD were eliminated.5

Improvements in morbidity and quality of life would also besubstantial. In order to achieve these goals, healthcare pro-viders must focus on reducing CVD risk factors such asoverweight and obesity, poor dietary habits, and physicalinactivity by helping individuals begin and maintain dietaryand PA changes. Each year �$44 billion, including $33billion in medical costs and $9 billion in lost productivity dueto heart disease, cancer, stroke, and diabetes, is attributable topoor nutrition.6 In the year 2000, the annual estimated directmedical cost of physical inactivity was $76.6 billion.1

There are considerable published data to strongly support thebenefits of PA and dietary changes as a means to decrease themorbidity and mortality of CVD and stroke in adults. Such dataare presented and discussed in detail in the statements from theAmerican Heart Association (AHA)7 and other sources. Notablestatements and studies include, but are not limited to, thestatement on exercise (AHA),8 the statement on PA interventionstudies (AHA),9 the statement on diet and lifestyle recommen-dations (AHA),10 the 2005 Dietary Guidelines for Americans,11

and the recommendation on PA and public health.12 Despite theabundance of data supporting the benefits of lifestyle changesfor CVD, it is striking that Americans are increasingly morechallenged with the growing burdens of excess body weight,limited PA, and suboptimal dietary habits. These lifestyle prob-lems are also associated with many chronic diseases other thanCVD and stroke, including type 2 diabetes, osteoporosis, depres-sion, and many cancers.

Cardiovascular risk factors can be combated and controlledby adherence to current lifestyle recommendations. Oneimportant example of success achieved in improving lifestylehabits is the achieved decline in prevalent tobacco use from42.4% to 20.5% of American adults between 1965 and2007.13 Although work remains in this regard, the success oftobacco cessation efforts provides a strong basis for optimismthat a concerted evidence-based program of education, policychange, and individual interventions could successfully im-prove dietary and PA habits in the United States.

The purpose of this scientific statement is to provideevidence-based recommendations on implementing PA anddietary interventions among adult individuals, includingadults of racial/ethnic minority and/or socioeconomicallydisadvantaged populations. The most efficacious and effec-tive strategies are summarized, and guidelines are provided totranslate these strategies into practice. Individual, provider,and environmental factors that may influence the design ofthe interventions, as well as implications for policy and forfuture research, also are briefly addressed.

Description of Data Search Strategies andEvidence Rating SystemTo identify articles concerned with diet and PA behavior changeinterventions in individuals, literature searches were performedin 5 databases; MEDLINE, CINAHL, Cardiosource ClinicalTrials, Cochrane Library, and PsycINFO. Included studies werelimited to adult humans (defined as �18 years of age); Englishlanguage; randomized controlled or quasi-experimental designsor meta-analyses; focused on the effects of diet or PA interven-tions on weight, blood pressure (BP), PA level, aerobic resis-

tance exercise, fitness, or consumption of calories, fruits, vege-tables, fiber, total fat, saturated fat, cholesterol or salt; andpublished between January 1997 and May 2007. A few land-mark studies that predate 1997 publication were included in ourreview. Despite extensive search efforts, all relevant studies maynot have been identified; overall studies are representative andcapture the state of the field.

Unpublished reports or reports published only in abstract formwere not included. There was considerable variation in thedirection and strength of findings within the studies reviewed;however, an effect of bias against publication of studies with nullresults cannot be ruled out. Studies were restricted to thoseconducted in the United States because societal and culturalfactors can affect feasibility and success of particular interven-tion strategies; nonetheless, most of the findings may be gener-alizable to other developed nations. Feeding trials, observationalstudies of specific nutrients, and observational studies of aerobiccapacity were excluded. Given the varying goals and outcomesof the different identified intervention studies, when possible weused a common measure of effect size (ES) to quantify andcompare the success of each intervention.14 Recommendationsfollow the AHA and the American College of Cardiologymethods of classifying the evidence (Table 1).

FindingsDetails of studies of behavioral change interventions andrelated PA and dietary outcomes are presented in Tables 2and 3. Because cognitive-behavioral strategies for promotingchange are integrated across all reports, the studies in Tables2 and 3 are organized according to the format of theintervention delivery. The majority of studies assessedchanges in body weight and/or specific eating patterns (fruits/vegetables, dietary fat). Except for studies using standard behav-ioral interventions for weight loss, in which daily calorie and fatgram goals are provided, most studies did not target total energyintake. As shown in Tables 2 and 3, the ES for the between-

Table 1. Definition of Classes and Levels of Evidence Used inDietary and Physical Activity Lifestyle ChangesRecommendations226

Class I Conditions for which there is evidence for and/orgeneral agreement that the procedure or treatment

is useful and effective.

Class II Conditions for which there is conflicting evidenceand/or divergence of opinion about the

usefulness/efficacy of a procedure or treatment.

Class IIa Weight of evidence or opinion is in favor of theprocedure or treatment.

Class IIb Usefulness/efficacy is less well established byevidence or opinion.

Class III Conditions for which there is evidence and/orgeneral agreement that the procedure or treatmentis not useful/effective and in some cases may be

harmful.

Level of Evidence A Data derived from multiple randomized clinical trials.

Level of Evidence B Data derived from a single randomized trial ornonrandomized studies.

Level of Evidence C Expert opinion or case studies.

Artinian et al Promoting Physical Activity and Dietary Changes 407

Tabl

e2.

RCTs

ofIn

terv

entio

nsto

Prom

ote

PAan

dDi

etar

yLi

fest

yle

Chan

ge:N

onm

inor

itySa

mpl

es

Refe

renc

e(s)

,Ye

ar,

Stud

yDe

sign

/Du

ratio

n(N

)Po

pula

tion/

Sam

ple

Inte

rven

tion

Outc

omes

Calo

ries/

Fat/F

ruits

and

Vege

tabl

es/F

iber

/Sod

ium

PAW

eigh

tBP

/Cho

lest

erol

/Glu

cose

/He

mog

lobi

nA1

c

Prin

t-on

lyde

liver

yst

rate

gies

Hunt

etal

,118

2004

,2-

grou

pRC

T/12

mo

(N�

5473

)

Prim

ary

care

prac

tice

subj

ects

with

mild

lyco

ntro

lled

HTN,

58%

wom

en,

mea

nag

e69

y,�

90%

whi

te.

Rete

ntio

n:52

%.

I:2

educ

atio

nalp

acke

tsse

nt3

mo

apar

t;fir

stfo

cuse

don

HTN

and

lifes

tyle

,se

cond

onm

edic

atio

nad

here

nce

and

hom

eBP

mon

itorin

gw

ithBP

log;

both

incl

uded

lette

rfro

mPC

P.Su

bjec

tsfro

mbo

thgr

oups

rand

omly

sele

cted

toha

veBP

mea

sure

dan

dco

mpl

ete

surv

ey.I

nter

vent

ion

grou

psc

ored

high

eron

HTN

know

ledg

equ

iz(7

.48�

1.6

vs7.

06�

1.6,

P�0.

019)

.C:

Subj

ects

rece

ived

usua

lcar

e.

……

…BP

:C

137/

77vs

I135

/77,

P�0.

229.

Mar

cus

etal

,79

1998

,2-

grou

pRC

T/6

mo

(N�

194)

76%

fem

ale,

mea

nag

e44

.3y,

93.8

%w

hite

,82

%em

ploy

ed,

mea

n12

.5m

inof

mod

erat

ele

velP

Aat

base

line.

C:4

self-

help

book

lets

prom

otin

gPA

mai

led

tosu

bjec

ts.

I:Co

mpu

ter-

gene

rate

d,in

divi

dual

lyta

ilore

dre

ports

and

self-

help

man

uals

mat

ched

tost

age

ofm

otiv

atio

nalr

eadi

ness

.Re

ports

cons

iste

dof

feed

back

abou

t(1

)st

age

ofre

adin

ess

for

PA;

(2)

leve

lof

self-

effic

acy,

deci

sion

alba

lanc

e,an

dus

eof

cogn

itive

-beh

avio

ralp

roce

sses

;(3

)co

mpa

rativ

efe

edba

ck;

and

(4)

prog

ress

sinc

ela

stas

sess

men

t.M

otiv

atio

nally

mat

ched

man

uals

acco

mpa

nied

repo

rts;

sent

bym

ail.

…PA

:Igr

oup:

mea

nof

97.6

min

ofPA

/wk

com

pare

dw

ithIg

roup

(151

.4m

in/w

k);A

signi

fican

tlygr

eate

rnum

bero

fIsu

bjec

tsre

ache

dre

com

men

ded

PAth

anC

grou

p.

……

Grou

p-ba

sed

inte

rven

tion

deliv

ery

stra

tegi

es

Alda

naet

al,11

3

2006

,2-

grou

pRC

T/6

mo

(N�

348)

70%

wom

en,

mea

nag

e50

y,93

%w

hite

,BM

I31

–33.

Rete

ntio

n:In

terv

entio

n88

%,

cont

rol9

5%.

I:40

-lect

ure

cour

seov

er4

wks

,fo

cus

onnu

tritio

nan

dPA

.Te

xtbo

okan

dw

orkb

ook

follo

wed

curr

icul

umto

pics

prov

ided

,in

clud

edas

sign

men

ts.

Only

with

in-g

roup

chan

ges

repo

rted,

allP

valu

essi

gnifi

cant

.C:

Not

desc

ribed

.

……

Wei

ght

loss

:C

�0.

5vs

I�4.

5kg

,P�

0.00

01.

SBP/

DBP

mm

Hg:

�5/

�5.

5vs

�4/

�3.

8,P�

0.00

01Ch

oles

tero

l:�

6vs

�11

,P�

0.00

4Gl

ucos

e:�

3vs

�1,

P�0.

005.

Ande

rsen

etal

,56

1999

,2-

grou

pRC

T/1

y(N

�40

)

Wom

en,

mea

nag

e43

y;BM

I32.

9.Re

tent

ion:

98%

at16

wks

,82

.5%

at68

wks

.

Stru

ctur

edae

robi

cex

erci

se(S

AE)�

low

-fat

diet

:w

eekl

yae

robi

cex

erci

secl

asse

sfo

r16

wks

.M

oder

ate

lifes

tyle

activ

ity�

low

-fat

diet

:w

eekl

ygr

oup

sess

ions

focu

sed

onm

oder

ate

PA,

kept

daily

reco

rds,

wor

epe

dom

eter

s,re

ceiv

edgr

aphs

ofPA

and

feed

back

.

……

Wei

ght

loss

:SA

Egr

oup

�8.

3kg

vs�

7.9

kgat

16w

ks,

P�0.

08;

ES�

0.57

.At

1ye

ar,

SAE

rega

ined

1.6

vs0.

08kg

.

SBP,

chol

este

roli

mpr

ovem

ent

with

ingr

oups

(P�

0.00

1)at

16w

ks,

NSD

betw

een

grou

ps.

Burk

eet

al,24

2006

,4-

grou

pRC

T/18

mo

(N�

182)

87%

wom

en,

mea

nag

e44

y,29

.7%

min

ority

,BM

I34.

Rete

ntio

n:86

%.

Stan

dard

beha

vior

alw

eigh

tlo

sstre

atm

ent

(SBT

)de

liver

edto

all4

grou

ps:

(1)

SBT�

lact

o-ov

o-ve

g(L

OV)

diet

/not

pref

erre

d,(2

)SB

T�LO

Vdi

et/p

refe

rred

,(3

)SB

T�st

anda

rdw

eigh

tlo

ssdi

et/n

otpr

efer

red,

(4)

SBT�

stan

dard

wei

ght

loss

diet

/pre

ferr

ed.

SBT

incl

udes

goal

setti

ng,

self-

mon

itorin

g,an

dfe

edba

ck.

Inte

rven

tion

12m

o,st

udy

give

s6-

mo

repo

rt.

……

Wei

ght

loss

bydi

etgr

oups

:�

7.0–

7.5

kg,

NSD

bydi

etor

pref

eren

cegr

oup;

ES�

0.03

.

LDL:

SBT

0.05

vsSB

T�LO

V–0

.16,

P�0.

013.

Care

lset

al,23

2004

,2-

grou

pRC

T/1

y(N

�44

)

100%

wom

en,

mea

nag

e54

.7y,

race

not

repo

rted,

44.5

%co

llege

degr

ee,

33.3

%in

com

e�

$30

000,

mea

nBM

I36.

4.

Life

styl

ech

ange

(LC)

:24

grou

pse

ssio

nsto

chan

gew

eigh

tan

dPA

;5

com

pone

nts:

lifes

tyle

,ex

erci

se,

attit

udes

,re

latio

nshi

ps,

and

nutri

tion.

Focu

sed

onse

lf-m

onito

ring,

cont

rolli

ngst

imul

i,PA

,nu

tritio

ned

ucat

ion,

mod

ifyin

gse

lf-de

feat

ing

thou

ghts

and

nega

tive

emot

ions

,se

tting

real

istic

goal

s,re

latio

nshi

ps,

rela

pse

prev

entio

n,an

dw

eigh

tm

aint

enan

ce.

Life

styl

ech

ange

�se

lf-co

ntro

lski

llstra

inin

g:Li

fest

yle

chan

geas

abov

epl

usa

com

bina

tion

ofdi

dact

icin

stru

ctio

n,in

divi

dual

activ

ities

,an

dw

eekl

you

t-of

-cla

ssas

sign

men

tsto

stre

ngth

ense

lf-co

ntro

l.

Calo

ries:

Aver

age

daily

calo

ricin

take

decr

ease

d47

2ca

lin

both

grou

ps,

P�0.

05.

Perc

ent

ofen

ergy

from

fat

and

satu

rate

dfa

tde

crea

sed

by5.

4%an

d2.

7%,

resp

ectiv

ely;

P�0.

05.

NSD

betw

een

grou

ps.

PAan

dfit

ness

:bo

thgr

oups

incr

ease

dm

axim

alox

ygen

cons

umpt

ion,

tread

mill

time,

and

wee

kly

leis

ure

time

activ

ityP�

0.05

.NS

Dbe

twee

ngr

oups

.

Wei

ght

loss

:M

ean

wei

ght

loss

inbo

thgr

oups

was

6.2

kg,

P�0.

05.

NSD

betw

een

grou

ps.

BP:B

oth

grou

psha

da

mea

nde

crea

sein

SBP

of8

mm

Hgan

din

DBP

of7.

9m

mHg

,P�

0.05

.NSD

betw

een

grou

ps.

Chol:

Forb

oth

grou

psLD

Lde

crea

sed

anav

erag

eof

10.6

mg/

dL.N

SDbe

twee

ngr

oups

.

(Con

tinue

d)

408 Circulation July 27, 2010

Tabl

e2.

Cont

inue

d

Refe

renc

e(s)

,Ye

ar,

Stud

yDe

sign

/Du

ratio

n(N

)Po

pula

tion/

Sam

ple

Inte

rven

tion

Outc

omes

Calo

ries/

Fat/F

ruits

and

Vege

tabl

es/F

iber

/Sod

ium

PAW

eigh

tBP

/Cho

lest

erol

/Glu

cose

/He

mog

lobi

nA1

c

Hesh

kaet

al,12

3,12

4

2003

,2-

grou

p,m

ultic

ente

rRC

T/2

y(N

�42

3)

�80

%w

omen

,ag

e44

–45

y,BM

I34.

Self-

help

prog

ram

(SH)

:tw

o20

-min

coun

selin

gse

ssio

nsw

ithnu

tritio

nist

and

prov

isio

nof

self-

help

reso

urce

s.Co

mm

erci

alw

eigh

tlo

sspr

ogra

m:

food

and

activ

itypl

ans,

cogn

itive

rest

ruct

urin

gbe

havi

orm

odifi

catio

npl

an,

wee

kly

mee

tings

over

104

wks

.

……

Wei

ght

loss

:SH

grou

p�

1.3

vsCo

mm

erci

algr

oup

�4.

3kg

,P�

0.00

1at

12m

o;�

0.2

vs�

2.9

kgat

2y,

P�0.

001;

ES�

0.16

.

…

Jaki

cic

etal

,109

1999

,3-

grou

pRC

T/18

mo

(N�

148)

Wom

en,

mea

nag

e37

y,BM

I32.

8.Re

tent

ion:

78%

.

Beha

vior

alw

eigh

tco

ntro

lpro

gram

com

bine

dw

ith(1

)Lo

ng-b

out

exer

cise

(LB)

;(2

)m

ultip

lesh

ort-

bout

exer

cise

(SB)

;or

(3)

mul

tiple

shor

t-bo

utex

erci

sew

ithho

me

exer

cise

equi

pmen

t(S

BEQ)

(pro

vide

dtre

adm

ill).

…VO

2si

gnifi

cant

lyin

crea

sed

com

pare

dw

ithba

selin

e,NS

Dam

ong

grou

ps.

Wei

ght

loss

inSB

EQ�

7.4

kgvs

SB�

3.7,

P�0.

05;

NSD

from

LBgr

oup

�5.

8;ES

�16

.

…

Jeffe

ryet

al,25

1998

,5-

grou

pRC

T/18

mo

(N�

193)

�80

%fe

mal

e,ag

e�

40y,

�80

%w

hite

,BM

I31.

Rete

ntio

n:78

%.

(1)

Stan

dard

beha

vior

alth

erap

yfo

rw

eigh

tlo

ss(S

BT);

(2)

SBT�

supe

rvis

edw

alks

(SW

)3/

wk;

(3)

SBT�

SW�

pers

onal

train

er(P

T)w

orke

dw

ith2–

3su

bjec

tsdu

ring

wal

ks;

(4)

SBT�

SW�

mon

etar

yin

cent

ives

(I)pa

id$1

–$5

for

wal

ks(In

);an

d(5

)SB

T�SW

�PT

�In

rece

ived

allo

fth

eab

ove.

SBT�

wee

kly

grou

pse

ssio

ns�

24,

mon

thly

ther

eafte

rfo

r1

y.Da

ilyca

lorie

/fat

goal

s,PA

250–

1000

kcal

/wk.

…PA

:su

bjec

tsin

allg

roup

sac

hiev

edst

udy

goal

of10

00kc

al/w

k.

Wei

ght

loss

inkg

:SB

T�

7.6

vsSB

T�SW

�3.

8vs

SBT�

SW�

PT�

2.9

vsSB

T�SW

�I�

4.5

vsSB

T�SW

�PT

�I�

5.1

kg,

Trea

tmen

tgr

oups

diffe

renc

efro

mba

selin

eto

18m

ow

assi

gnifi

cant

,P�

0.03

.Th

eSB

Tgr

oup

had

grea

ter

loss

es.

…

Writ

ing

Grou

pof

the

PREM

IER

Colla

bora

tive

Rese

arch

Grou

p,26

2003

,3-

grou

pRC

T/6

mo

(N�

810)

Adul

tsw

ithst

age

1hy

perte

nsio

nor

optim

alBP

,34

%bl

ack,

62%

wom

en,

mea

nag

e50

year

s,ap

prox

imat

ely

10%

�$3

000

0an

nual

inco

me.

Subj

ects

’go

als

for

EST

and

EST�

DASH

wer

ew

eigh

tlo

ss�

15lb

for

subj

ects

with

BMI�

25,

�18

0m

inut

es/w

km

oder

ate

inte

nsity

PA,

daily

inta

keof

�10

0m

EqNa

,da

ilyin

take

�1

ozal

coho

lfor

men

and

1 ⁄2oz

for

wom

en.

Esta

blis

hed

(EST

):18

face

-to-

face

cont

acts

(14

grou

pm

eetin

gsan

d4

indi

vidu

alse

ssio

ns).

Diar

ies

used

tore

cord

PA,

calo

ries,

and

Na.

Esta

blis

hed

plus

DASH

(EST

�DA

SH):

Subj

ects

rece

ived

alli

nES

Tpl

usin

stru

ctio

nan

dco

unse

ling

abou

tDA

SHdi

et;

diet

ary

goal

sfo

rF/

V,lo

w-f

atda

iry,

satu

rate

dfa

t,an

dto

talf

at.

Diar

ies

used

tore

cord

PA,

calo

rie,

Na,

F/V,

dairy

,an

dfa

t.Ad

vice

only

(A):

Diet

itian

prov

ided

a30

-min

indi

vidua

lses

sion

onno

npha

rmac

olog

ical

fact

ors

that

affe

ctBP

and

prov

ided

prin

ted

educ

atio

nal

mat

eria

ls.Co

unse

ling

onbe

havio

rch

ange

notp

rovid

edbu

thad

4in

divid

ual

coun

selin

gse

ssio

nson

lifes

tyle

chan

ge.

DASH

diet

incl

uded

9–12

serv

ings

F/V

per

day,

low

-fatd

airy

2–3

serv

ings

/d,

�7%

ener

gysa

tura

ted

fat,

and

�25

%en

ergy

tota

lfat

.

F/V

serv

ings

/d:

Chan

gefro

mba

selin

e,0.

5fo

rA,

0.5

for

EST,

3.0

for

EST�

DASH

.ES

Tvs

A,P�

0.79

;al

loth

erco

mpa

rison

sP�

0.00

1.To

talf

at,

%kc

al:

�1.

0fo

rA,

�3.

9fo

rES

T,�

9.5

EST�

DASH

.Al

lcom

paris

ons

P�0.

001.

PAkc

al/k

g/d:

NSD.

Wei

ght

loss

:Ch

ange

from

base

line:

�1.

1kg

inA,

�4.

9kg

inES

T,�

5.8

kgin

EST�

DASH

;ES

Tvs

Aan

dES

T�DA

SHvs

A,P�

0.00

1;ES

Tvs

EST�

DASH

,P�

0.07

.

Prev

alen

ceof

high

BPat

6m

o:26

%in

Agr

oup,

17%

inES

Tgr

oup,

12%

inES

T�DA

SHgr

oup

(diff

eren

cebe

twee

nA

and

EST,

P�0.

01;

betw

een

Aan

dES

T�DA

SH,

P�0.

001;

betw

een

EST

and

EST�

DASH

,P�

0.12

).

McM

anus

etal

,27

2001

,2-

grou

pRC

T/18

mo

(N�

101)

�90

%fe

mal

e,m

ean

age

44y,

�88

%w

hite

,BM

I34.

Rete

ntio

n:20

%vs

54%

at18

mo.

Low

-fat

(LF)

diet

:20

%of

kcal

.M

oder

ate

fat

(MF)

:35

%of

kcal

,M

edite

rran

ean

diet

.Bo

thgr

oups

:w

eekl

ygr

oup

educ

atio

nalc

lass

esto

addr

ess

beha

vior

alm

odifi

catio

nsk

ills

and

PA;

self-

mon

itore

din

wee

kly

diar

ies,

feed

back

prov

ided

.

Tota

lfat

(%kc

al):

LF30

%vs

MF

35%

,P�

0.03

.…

Wei

ght

loss

:LF

�2.

9vs

MF

4.8

kgat

18m

o,P�

0.00

1;ES

�0.

33.

…

Sim

kin-

Silv

erm

anet

al,66

2003

,2-

grou

pRC

T/4.

5y

(N�

535)

Wom

en(p

eri-

topo

stm

enop

ausa

l),pr

edom

inan

tlyw

hite

,35

.5%

over

wei

ght,

11%

obes

e.Re

tent

ion

at5

y:95

%.

C:He

alth

educ

atio

npa

mph

let

and

asse

ssm

ent

only

at6,

18,

30,

42,

and

54m

o.Li

fest

yle

inte

rven

tion

(LI):

Phas

e1:

15gr

oup

mee

tings

/20

wks

,lif

esty

lech

ange

s,m

odes

tw

eigh

tlo

ss,

and

PA;

Phas

e2:

6gr

oup

mee

tings

inm

o6–

54;

mai

land

tele

phon

eF/

U.In

divi

dual

nutri

tion

cons

ulta

tion

offe

red

tolo

wer

LDL

chol

este

rol.

Kcal

:C

�24

.8vs

LI�

159.

6kc

al,

P�0.

01;

ES�

0.11

.En

ergy

expe

nditu

re:

C�

113.

3vs

274.

9kc

al,

P�0.

001;

ES�

0.14

.

Wei

ght

loss

:55

%of

LIgr

oup

wer

eat

orbe

low

base

line

wei

ght

com

pare

dw

ith26

%of

Cgr

oup,

P�0.

001.

Mea

nw

eigh

tch

ange

inLI

grou

pw

as0.

1kg

belo

wba

selin

eco

mpa

red

with

mea

nw

eigh

tga

inof

2.4

kgin

Cgr

oup.

…

(Con

tinue

d)

Artinian et al Promoting Physical Activity and Dietary Changes 409

Tabl

e2.

Cont

inue

d

Refe

renc

e(s)

,Ye

ar,

Stud

yDe

sign

/Du

ratio

n(N

)Po

pula

tion/

Sam

ple

Inte

rven

tion

Outc

omes

Calo

ries/

Fat/F

ruits

and

Vege

tabl

es/F

iber

/Sod

ium

PAW

eigh

tBP

/Cho

lest

erol

/Glu

cose

/He

mog

lobi

nA1

c

Toob

ert

etal

,67

2005

,2-

grou

pRC

T/6

mo

(N�

279)

Post

men

opau

sal

wom

enw

ithty

pe2

DM,

�90

%w

hite

,BM

I35.

Rete

ntio

n:88

%.

UC:

ongo

ing

diab

etes

care

from

MD

Med

iterr

anea

nLi

fest

yle

Prog

ram

(MLP

):lif

esty

lech

ange

aim

edat

beha

vior

alris

kfa

ctor

saf

fect

ing

CHD

;2.

5-d

retr

eat

follo

wed

byw

eekl

y4-

hm

eetin

gsfo

r6

mo.

Focu

s:di

et,

PA,

stre

ssm

anag

emen

t,so

cial

supp

ort.

Tota

lfat

(g):

UC16

2.1

vsM

LP46

.6g,

P�0.

001;

ES�

20.

Frui

tse

rvin

gs/d

:UC

1.6

vs2.

2,P�

0.00

1Ve

geta

ble

serv

ings

/d:

UC2.

0vs

2.6,

P�0.

001.

PA(M

ETs�

dura

tion�

days

):55

.9UC

vs80

.9M

LP,

P�0.

009.

Wei

ght:

UC93

.4vs

MLP

91.7

kg,

P�0.

004.

…

Wad

den

etal

,72

1998

,4-

grou

pRC

T/1

y(N

�99

)

Wom

en,

mea

nag

e42

y,BM

I36.

Rete

ntio

n:60

.2%

.

Cogn

itive

-beh

avio

ral

trea

tmen

tfo

rw

eigh

tlo

ssde

liver

edin

28w

eekl

yse

ssio

nsfo

llow

edby

10bi

wee

kly

sess

ions

com

bine

dw

ithca

loric

-res

tric

ted

diet

plus

1of

4ex

erci

segr

oups

:(1

)ae

robi

cex

erci

se,

(2)

stre

ngth

trai

ning

�ae

robi

c,(3

)st

reng

thtr

aini

ng,

or(4

)no

exer

cise

beyo

ndlif

esty

leac

tivity

.

……

Wei

ght

loss

:4

grou

ps10

.6–1

1.4

kg,N

SD;a

t1y

35%

–55%

ofw

eigh

tre

gain

ed,

NSD.

…

Wad

den

etal

,28

2005

,4-

grou

pRC

T/1

y(N

�22

4)

Men

&w

omen

,m

ean

age

43.6

y,65

%w

hite

,BM

I37.

8.

Alls

ubje

cts

had

diet

of12

00–1

500

kcal

/dan

dex

erci

se30

min

/dm

ost

days

ofth

ew

eek.

Sibu

tram

ine

Alon

e(S

ibA)

:8

brie

fvi

sits

with

PCP

at1,

3,6,

10,

18,

40,

52w

ks.

Rece

ived

dose

ofsi

butra

min

eat

wk

1;re

ceiv

edpr

int

mat

eria

lsab

out

fitne

ss.

Life

styl

eM

odifi

catio

nAl

one

(LM

A):

Wkl

ygr

oup

mee

tings

from

wks

1–19

,ev

ery

2w

ksfr

omw

ks20

–40,

follo

w-u

pvi

sit

wk

52.

Dai

lyse

lf-m

onito

ring

offo

odin

take

and

PA,

whi

chw

ere

revi

ewed

atw

kly

mee

tings

.Co

mbi

ned

Ther

apy

(CT)

:Sa

me

2tr

eatm

ents

asgr

oups

abov

e.Si

butr

amin

epl

usBr

ief

Ther

apy.

(Sib

�BT

):Si

butr

amin

eas

ingr

oup

1an

dm

etw

ithPC

P10

–15

min

.on

sam

esc

hedu

leas

grou

pm

eetin

gs.

……

Wei

ght

loss

:CT

12.1

�9.

8kg

vsSi

bA5.

0�7.

4kg

vsLM

A6.

7�7.

9kg

vsSi

b�BT

,7.

5�8.

0kg

,P�

0.00

1.Su

bjec

tsin

CTgr

oup

who

self-

mon

itore

dfre

quen

tly:

wei

ght

loss

18.1

�9.

8kg

vs7.

7�7.

5kg

,P�

0.04

.

…

Win

get

al,29

1999

,4-

grou

pRC

T/10

mo

(N�

166)

Wom

enan

dm

en,

age

�42

y,�

90%

whi

te,

BMI

31.2

.Re

tent

ion:

75%

–95%

.

(1)

Recr

uite

dal

one

and

stan

dard

beha

vior

alth

erap

yfo

rw

eigh

tlo

ssS

BT;

(2)

recr

uite

dal

one

and

SBT�

soci

alsu

ppor

t;(3

)re

crui

ted

with

frie

nds

and

SBT;

(4)

recr

uite

dw

ithfr

iend

s&

SBT�

soci

alsu

ppor

t.SB

Tin

clud

esgr

oup

sess

ions

;se

lf-m

onito

ring

calo

ries,

fat,

and

PAin

wee

kly

diar

ies;

and

feed

back

.So

cial

supp

ort:

incl

uded

intr

agro

upac

tiviti

esan

din

terg

roup

com

petit

ion

for

grou

ps2

and

4.

……

Wei

ght

loss

:Re

crui

ted

with

frien

ds�

7.7

kg,

recr

uite

dal

one

�4.

3kg

,P�

0.00

1;ES

�0.

26.

…

Yeh

etal

,6820

03,

2-gr

oup

RCT/

2y

(N�

80)

Wom

en,a

ge30

–60

y,BM

I36.

3an

d37

.9.

Rete

ntio

n:33

%SB

I,35

%CB

.

Offic

e-ba

sed

coun

selin

gw

ithdi

etiti

an(O

BC):

6in

terv

entio

nse

ssio

nsov

er6

mo�

offe

rof

6m

ore.

Skill

sba

sed

inte

rven

tion

(SBI

):tw

o90

-min

dida

ctic

sess

ions

rela

ted

todi

etan

dbe

havi

or;

addi

tiona

lse

ssio

nsfo

rte

chni

cal

skill

build

ing

(sup

erm

arke

t,re

stau

rant

s);

tele

phon

ean

dE-

mai

lac

cess

todi

etiti

anfo

rre

stof

12m

o.

Satu

rate

dfa

t(g

):OB

C�

0.08

vsSB

I�

4.2

gat

24m

o,P�

0.07

.…

Wei

ght

loss

:OB

C�

4.0

vsSB

I�

1.7

at6

mo,

P�0.

05;

1.1

vs�

0.6

at24

mo.

NS.

…

(Con

tinue

d)

410 Circulation July 27, 2010

Tabl

e2.

Cont

inue

d

Refe

renc

e(s)

,Ye

ar,

Stud

yDe

sign

/Du

ratio

n(N

)Po

pula

tion/

Sam

ple

Inte

rven

tion

Outc

omes

Calo

ries/

Fat/F

ruits

and

Vege

tabl

es/F

iber

/Sod

ium

PAW

eigh

tBP

/Cho

lest

erol

/Glu

cose

/He

mog

lobi

nA1

c

Indi

vidu

al-b

ased

inte

rven

tion

deliv

ery

stra

tegi

es

Amm

erm

anet

al,98

2003

,2-

grou

pcl

uste

rra

ndom

ized

trial

,8

rura

lhea

lthde

partm

ents

/12

mo

(N�

468)

71%

fem

ale,

mea

nag

e55

y,80

%w

hite

,75

%HS

educ

atio

n.

Subj

ects

inbo

thgr

oups

wer

ein

form

edof

chol

este

rol

resu

ltsby

lette

r;if

lipid

shi

gh,

they

wer

ein

form

edth

eyne

eded

trea

tmen

t.Sp

ecia

lin

terv

entio

n(S

I):(1

)Pu

blic

heal

thnu

rse

dire

cted

com

pone

ntus

ing

Food

for

Heal

thPr

ogra

mdu

ring

3co

unse

ling

visi

ts;

(2)

refe

rral

toa

loca

lnu

triti

onis

tif

lipid

sre

mai

ned

elev

ated

at3

mo

F/U;

(3)

are

info

rcem

ent

prog

ram

durin

g2n

dha

lfof

inte

rven

tion—

1te

leph

one

call

from

nurs

ean

d2

new

slet

ters

.St

ruct

ured

,in

divi

dual

lyta

ilore

ddi

etar

yco

unse

ling

bynu

rse

faci

litat

edby

adi

etar

yris

kas

sess

men

t,ill

ustr

ated

goal

shee

ts,

and

aSo

uthe

rnst

yle

cook

book

.M

inim

alin

terv

entio

n(M

I):O

ther

than

initi

alle

tter

abou

tch

oles

tero

lre

sults

,ot

her

inte

rven

tion

activ

ities

not

desc

ribed

.

Diet

ary

Risk

Asse

ssm

ent

Scor

e2.

1un

itsbe

tter

inth

eSI

vsM

I,P�

0.00

5.

…NS

Din

wei

ght

loss

.Re

duct

ion

into

talc

hole

ster

olsi

mila

rin

both

grou

ps:

18.4

mg/

dLin

SIvs

15.6

mg/

dLin

MI,

P�0.

06.

Burk

eet

al,30

2005

,2-

grou

pRC

T/14

wks

(N�

65)

�60

%m

ale,

94%

whi

te,

BMI

38–4

5.Re

tent

ion:

98%

.

UC:

Usua

lclin

ical

care

.I:

Tele

phon

e-de

liver

ed,

self-

effic

acy–

base

dco

unse

ling

toim

prov

ead

here

nce

toa

chol

este

rol-

low

erin

gdi

et,

6se

ssio

nsov

er12

wks

,in

clud

edgo

alse

tting

,se

lf-m

onito

ring

with

feed

back

,se

lf-ef

ficac

yen

hanc

emen

t.

Fat

chan

gesc

ore:

UC2.

3vs

I�

10.4

gP�

0.03

5;ES

�0.

29.

Satu

rate

dfa

tch

ange

scor

e:UC

0.18

vsI�

23g,

P�0.

045;

ES�

0.28

.

……

LDL-

Cch

ange

scor

e:UC

0.25

vsI0

.42

mg/

dL,

P�0.

013;

ES�

0.30

.

Delic

hats

ios

etal

,130

2001

,2-

grou

pcl

uste

rra

ndom

ized

trial

/3m

o(N

�50

4)

70%

fem

ale,

91%

whi

te,

mea

nag

e54

y.

C:Us

ualP

CPpr

actic

eI:

3co

mpo

nent

s—pe

rson

aliz

eddi

etre

com

men

datio

nsan

dst

age-

mat

ched

diet

-rel

ated

educ

atio

nal

book

lets

bym

ail,

prov

ider

endo

rsem

ent

ofth

ere

com

men

datio

ns,

and

2m

otiv

atio

nal

inte

rvie

wco

unse

ling

sess

ions

byte

leph

one.

Coun

selin

gen

cour

aged

goal

-set

ting

and

stag

eof

chan

gem

essa

ges.

F/V:

Chan

gein

F/V

inta

kein

Igro

upw

as0.

6(C

I,0.

3–0.

8)se

rvin

gs/d

high

erth

anco

ntro

lgro

up.

……

…

Ellio

tet

al,71

2007

,3-

grou

pcl

uste

rra

ndom

ized

trial

/12

mo

(N�

599)

97%

mal

efir

efig

hter

s,m

ean

age

41y,

91%

whi

te,

inco

me

�$5

000

0.

Both

inte

rven

tion

grou

psre

ceiv

eda

Heal

than

dFi

tnes

sgu

ide.

Team

cent

ered

:W

ork

grou

psw

ithde

sign

ated

lead

erm

etfo

r11

45-m

inse

ssio

nsan

dfo

llow

edsc

ripte

dle

sson

plan

son

nutr

ition

,PA

,en

ergy

bala

nce,

stre

ss,

slee

p,an

ddi

etar

ysu

pple

men

ts.

Mem

bers

rece

ived

base

line

PA,

diet

ary,

and

lab

asse

ssm

ent

resu

ltsfo

llow

edby

goal

setti

ng.

Mot

ivat

iona

lIn

terv

iew

ing

(MI):

Part

icip

ants

rand

omly

assi

gned

to1

of6

MI

coun

selo

rs;

4m

eetin

gsw

ithM

Ico

unse

lor

with

poss

ibili

tyof

5ho

urs

ofad

ditio

nal

inpe

rson

orte

leph

one

cont

act.

Cont

rol:

Rece

ived

only

test

resu

ltsw

ithex

plan

atio

nof

norm

alva

lues

;fr

eeto

use

own

initi

ativ

eto

alte

rlif

esty

le.

F/V:

Both

Team

and

MIh

adin

crea

sed

F/V

inta

ke(P

�0.

05).

PA:

Team

and

MIi

ncre

ased

no.

ofsi

t-up

sin

1m

in,

P�0.

05.

Wei

ght:

Both

Team

and

MI

gain

edw

eigh

t,bu

tle

ssga

inth

anUC

,P�

0.05

.

…

(Con

tinue

d)

Artinian et al Promoting Physical Activity and Dietary Changes 411

Tabl

e2.

Cont

inue

d

Refe

renc

e(s)

,Ye

ar,

Stud

yDe

sign

/Du

ratio

n(N

)Po

pula

tion/

Sam

ple

Inte

rven

tion

Outc

omes

Calo

ries/

Fat/F

ruits

and

Vege

tabl

es/F

iber

/Sod

ium

PAW

eigh

tBP

/Cho

lest

erol

/Glu

cose

/He

mog

lobi

nA1

c

Keys

erlin

get

al,22

7

2-gr

oup

RCT,

rand

omiz

atio

nof

clin

icia

n-pa

tient

grou

ps/1

y(N

�37

2)

42ph

ysic

ians

,�

66%

patie

ntpa

rtici

pant

sw

ithhi

ghch

oles

tero

lw

ere

fem

ale,

40%

blac

k,11

%Na

tive

Amer

ican

,M

ean

age

55.9

y,10

.6m

ean

yed

ucat

ion.

I:3

com

pone

nts—

(1)

clin

icia

n-di

rect

eddi

etar

yco

mpo

nent

;(2

)re

ferr

alto

alo

cald

ietit

ian

ifLD

L-C

rem

aine

del

evat

edat

4m

ofo

llow

-up

with

�2

risk

fact

ors

orCH

D;(3

)a

prom

ptfo

rth

ecl

inic

ian

toco

nsid

erdr

ugtre

atm

ent

base

don

LDL-

Cat

7m

ofo

llow

-up.

UC:

Phys

icia

nsw

ere

advi

sed

tom

anag

eth

eir

subj

ects

hype

rcho

lest

erol

emia

acco

rdin

gto

thei

rus

ualp

ract

ices

.

……

…To

talc

hole

ster

ol:A

t4-m

ofo

llow

-up,

tota

lcho

lest

erol

decr

ease

d0.

33m

mol

/Lin

the

Igro

upvs

0.21

mm

ol/L

inth

eC

grou

p(9

0%CI

,�

0.02

–0.

24m

mol

/L).

The

mea

nre

duct

ion

at1-

yfo

llow

-up

was

0.09

grea

ter

inth

eIg

roup

(90%

CI,

�0.

01–

0.19

mm

ol/L

).Ch

ange

sin

LDL-

Cw

ere

sim

ilar.

Mar

cus

etal

,69

2007

,3-

grou

pRC

T/12

mo

(N�

239)

82%

fem

ale,

90.3

%w

hite

,m

ean

age

44.5

y,m

ean

BMI

28.5

,60

%w

ithho

useh

old

inco

me

�$5

000

0.

C:He

alth

educ

atio

nm

ater

ialm

aile

don

sam

esc

hedu

leas

prin

tan

dte

leph

one;

subj

ects

com

plet

edPA

log

each

mon

th.

Tele

phon

e(T

):Su

bjec

tsre

ceiv

edPA

inte

rven

tion

mat

eria

lsth

roug

hte

leph

one

cont

act

with

ahe

alth

educ

ator

.Ed

ucat

orin

corp

orat

edin

divi

dual

lyta

ilore

dfe

edba

ckge

nera

ted

byan

expe

rtco

mpu

ter

syst

eman

dpr

ovid

edco

unse

ling

usin

ga

mot

ivat

ion

stag

ed-m

atch

edm

anua

l.M

ean

leng

thof

calls

was

13m

in;

90%

ofca

llsw

ere

com

plet

ed,

14co

ntac

tsov

erth

eco

urse

of12

mo.

Com

plet

edPA

log

each

mon

th.

Prin

t(P

):Su

bjec

tsre

ceiv

edin

divi

dual

lyta

ilore

dpr

inte

dre

ports

ofPA

,fe

edba

ckge

nera

ted

byex

pert

com

pute

rsy

stem

,al

ong

with

man

uals

mat

ched

toth

eir

stag

eof

read

ines

san

dtip

shee

ts,

14co

ntac

ts.

Com

plet

edPA

log

each

mon

th.

…PA

:At6

mo,

subj

ects

inT

grou

p(1

23.3

�97

.6)a

ndP

grou

p(1

29.5

�15

6.5)

repo

rted

larg

erin

crea

sein

min

ofPA

/wk

than

subj

ects

inC

grou

p(M

�77

.7�

101.

89),

P�0.

02.

At12

mo,

Pgr

oup

repo

rted

grea

term

oder

ate-

inte

nsity

PAco

mpa

red

with

Cgr

oup,

NSD

betw

een

Tan

dP

grou

ps.

……

Gree

net

al,31

2002

,2-

grou

pRC

T/6

mo

(N�

316)

52.5

%fe

mal

e,91

.5%

whi

te,

med

ian

age

44.5

y.

UC:

Note

leph

one

calls

.I:

320

–30

min

tele

phon

eca

llsm

onth

lyfo

r3

mo

from

beha

vior

alhe

alth

spec

ialis

tsw

hopr

ovid

edm

otiv

atio

nalc

ouns

elin

gin

acco

rdan

cew

ithst

ages

-of-

chan

gem

odel

,go

alse

tting

,as

sist

ance

with

prob

lem

-sol

ving

barr

iers

,an

did

entif

yre

sour

ces

for

supp

ort.

…PA

:Hi

gher

PAle

velp

erPA

CEsc

ore

for

I5.3

7vs

4.98

inUC

,P�

0.05

.

……

Orni

shet

al,22

2

1998

,2-

grou

pra

ndom

ized

invi

tatio

nald

esig

n/5

y(N

�35

)

91%

mal

ew

ithm

oder

ate

tose

vere

CHD,

Mea

nag

e59

.6y,

mea

n15

yof

educ

atio

n.

I:In

tens

ive

lifes

tyle

chan

ge,

10%

fat,

vege

taria

ndi

et,

aero

bic

exer

cise

,st

ress

man

agem

ent,

smok

ing

cess

atio

n,gr

oup

psyc

hoso

cial

supp

ort

for

5ye

ars.

C:Fo

llow

advi

ceof

phys

icia

nre

gard

ing

lifes

tyle

chan

ges.

Fat

inta

ke:

Igro

upfa

tin

take

decr

ease

d30

%to

8.5%

,P�

0.00

1;di

etar

ych

oles

tero

lde

crea

sed

211

to18

.6m

g/d,

P�0.

002

Cgr

oup

decr

ease

dfa

tin

take

30%

to25

%.

…W

eigh

t:Ig

roup

12.8

lblo

ssvs

noch

ange

inC

grou

p,P�

0.00

1.

LDL-

C:Ig

roup

decr

ease

s20

%vs

19.3

%in

Cgr

oup,

NSD

betw

een

grou

ps.

Arte

rials

teno

sis

decr

ease

dfro

mba

selin

ein

Igro

up,

P�0.

001

betw

een

grou

ps.

Ocke

neet

al,95

1999

,3-

grou

pRC

T/1

y

927

prim

ary

care

subj

ects

,45

prim

ary

care

inte

rnis

ts.

66%

fem

ale,

�90

%w

hite

,BM

I29.

Rete

ntio

nno

tre

porte

d.

UC:

Usua

lclin

ical

care

inpr

imar

yca

rese

tting

.Ph

ysic

ian

nutri

tion

coun

selin

gtra

inin

g:2

sess

ions

,a

2.5-

hsm

allg

roup

sess

ion

and

a30

-min

indi

vidu

aliz

edtu

toria

l;in

clud

eddi

dact

icin

stru

ctio

n,vi

deot

ape

obse

rvat

ion,

and

role

-pla

ying

.Ph

ysic

ian

nutri

tion

coun

selin

gtra

inin

g�of

fice-

supp

ort

prog

ram

:As

abov

e�of

fice-

supp

ort

prog

ram

desi

gned

toas

sist

MD

inca

rryi

ngou

tco

unse

ling

sequ

ence

,eg

,pa

tient

com

plet

edDi

etar

yRi

skAs

sess

men

tin

wai

ting

room

,lip

idre

sults

flagg

ed.

Note

:co

unse

ling

took

8.2

min

,5.

5m

inm

ore

than

cont

rolc

ondi

tion.

Fat

%kc

al:

Grou

p1

vs2

vs3

�0.

7%vs

�1.

0%vs

�2.

3%,

P�0.

11.

Satu

rate

dfa

t(%

kcal

):0.

0vs

�0.

4vs

�1.

1%,

P�0.

01;

ES�

0.10

.

…W

eigh

tlo

ss:

Grou

p1

vs2

vs3

0.0

vs�

1.0

vs�

2.3

kg,

P�0.

001.

LDL-

C:�

0.01

vs0.

02vs

�0.

11m

mol

/L,

P�0.

10.

Tota

lcho

lest

erol

:HD

Lra

tio:

0.1

vs0.

1vs

�0.

1m

g/dL

,P�

0.00

4. (Con

tinue

d)

412 Circulation July 27, 2010

Tabl

e2.

Cont

inue

d

Refe

renc

e(s)

,Ye

ar,

Stud

yDe

sign

/Du

ratio

n(N

)Po

pula

tion/

Sam

ple

Inte

rven

tion

Outc

omes

Calo

ries/

Fat/F

ruits

and

Vege

tabl

es/F

iber

/Sod

ium

PAW

eigh

tBP

/Cho

lest

erol

/Glu

cose

/He

mog

lobi

nA1

c

Pint

oet

al,12

520

05,

2gr

oup/

6m

o(N

�10

0)

85%

whi

te,

63%

fem

ale

BMI2

9.Re

tent

ion:

EA46

,BA

44.

Brie

fad

vice

(BA)

:Br

ief

advi

ceto

exer

cise

bya

clin

icia

nal

one.

Exte

nded

advi

ce(E

A):

Brie

fad

vice

toex

erci

sefro

ma

clin

icia

nsu

pple

men

ted

byte

leph

one-

base

dco

unse

ling

byhe

alth

educ

ator

s,co

unse

ling

tailo

red

tosu

bjec

t’sre

adin

ess

toin

crea

sePA

leve

lsas

wel

las

thei

rco

nvic

tion

and

conf

iden

ce;

used

mot

ivat

iona

lint

ervi

ewin

gte

chni

ques

.

…En

ergy

expe

nditu

re:

BA�

0.83

vsEA

�3.

8kc

al/w

k3

mo,

P�0.

03;

ES�

0.23

;6

mo,

P�0.

05,

ES�

0.20

.

……

Rich

ards

etal

,104

2006

,2-

grou

pRC

T/4

mo

(N�

437)

100%

colle

gest

uden

ts;

mea

nag

e20

.4y,

75%

wom

en,

96%

whi

te.

I:Su

bjec

tsre

ceiv

eda

pers

onal

ized

lette

rto

stag

eof

chan

ge,

ase

ries

of4

stag

e-ba

sed

new

slet

ters

spec

ific

toth

eir

stag

eof

chan

geat

base

line,

1m

otiv

atio

nali

nter

view

ing

sess

ion,

refe

rral

toa

nutri

tion

Web

site

,an

da

min

imum

of2

E-m

ailc

onta

cts

over

a4-

mo

perio

d.C:

Subj

ects

com

plet

edba

selin

ean

dfo

llow

ing

surv

eys

with

noad

ditio

nal

cont

act

from

stud

ype

rson

nel.

F/V:

Cons

umpt

ion

incr

ease

dby

1se

rvin

g.d

inIg

roup

asm

easu

red

bya

26-it

emFF

Qan

da

1-ite

mFF

Qvs

0.4

serv

ings

/din

Cgr

oup

per

the

1-ite

mFF

Qan

dno

chan

gepe

rth

e26

-item

FFQ.

……

…

Stev

ens

etal

,32

2003

,2-

grou

pRC

T/12

mo

(N�

616)

Wom

en,

mea

nag

e54

.4y,

91%

whi

te,

BMI

30.2

�7.

1.Re

tent

ion

I:89

%,

Con:

85%

.

C:Fo

cuse

don

brea

stse

lf-ex

amin

atio

n,in

divi

dual

sess

ion�

vide

otap

e,an

d2

F/U

tele

phon

eca

lls.

I:Tw

o45

-min

diet

coun

selin

gse

ssio

ns�

2br

ief

F/U

tele

phon

eco

ntac

ts,

with

goal

setti

ng,

feed

back

,pr

oble

m-s

olvi

ng,

and

mot

ivat

iona

lint

ervi

ewin

gst

rate

gies

;de

liver

edby

mas

ter’s

prep

ared

heal

thco

unse

lors

.

Fat

(%):

C38

.6%

vs34

.9%

,P�

0.00

1F/

V(s

ervi

ngs)

:C

3.4

vs4.

3,P�

0.00

1;ES

�0.

13.

……

…

Com

pute

r/In

tern

et-

base

din

terv

entio

nde

liver

yst

rate

gies

Ande

rson

etal

,33

2001

,2-

grou

pRC

T/6

mo

(N�

277)

96%

fem

ale,

96%

whi

te,

med

ian

inco

me

�$3

500

0.

C:No

expo

sure

tosu

perm

arke

tki

osks

.I:

Subj

ects

used

supe

rmar

ket

kios

k-ba

sed

self-

adm

inis

tere

d,co

mpu

ter-

base

dSC

Tin

terv

entio

n;pr

ovid

edpe

rson

aliz

edin

fo,

beha

vior

alst

rate

gies

,in

cent

ives

for

chan

ge,

and

feed

back

onpe

rson

algo

als.

Prog

ram

guid

ein

crea

sefib

er,

F/V,

and

redu

ced

fat

info

odpu

rcha

ses

thro

ugh

15w

eekl

yse

gmen

ts;

offe

red

food

coup

ons

of$8

–$12

/wk.

Fat,

fiber

,F/

V:Ig

roup

mor

elik

ely

than

Cgr

oup

toat

tain

goal

sfo

rfa

t,fib

er,

F/V.

……

…

Delic

hats

ios

etal

,17

2001

,2-

grou

pRC

T/6

mo

(N�

298)

72%

fem

ale,

45%

whi

te,

45%

blac

k,m

ean

age

45.9

5y,

BMI2

8.7,

85%

empl

oyed

.

C:Us

edan

inte

ract

ive,

com

pute

r-ba

sed

syst

emto

serv

eas

anat

-hom

em

onito

r,ed

ucat

or,

and

coun

selo

rre

gard

ing

diet

.Su

bjec

tsca

lled

syst

em1/

wk

for

6m

o;re

ceiv

edre

min

der

call

ifsu

bjec

tdi

dno

tca

llsy

stem

in2

wks

.I:

Used

sam

esy

stem

asC

exce

ptco

nver

satio

nfo

cuse

don

PA.

F/V:

Igro

upra

ised

no.

ofse

rvin

gsof

fruit

com

pare

dw

ithC

grou

p(C

I,4–

1.7)

.No

diffe

renc

esfo

rve

geta

bles

.Di

etar

yfib

erra

ised

by4.

0g/

dco

mpa

red

with

Cgr

oup

(CI,

1–7.

8).

……

…

Gold

etal

,122

2007

,2-

grou

pRC

T/12

mo

(N�

124)

98%

wom

en,

98%

whi

te,

age

47y,

BMI3

2.Re

tent

ion:

65%

inVT

rim,

77%

ineD

iets

.

VTrim

:Ac

cess

toth

erap

ist-

led

stru

ctur

edbe

havi

oral

wei

ght

loss

prog

ram

deliv

ered

onlin

e.eD

iets

.com

:Ac

cess

tose

lf-he

lpco

mm

erci

alw

eigh

tlo

sspr

ogra

mW

ebsi

te.

……

Wei

ght

loss

:VT

rim�

8.3

kgvs

eDie

t�

4.1

kgat

6m

os,

P�0.

004,

ES�

0.21

;at

12m

o,�

7.8

vs�

3.4,

P�0.

002,

ES�

0.16

.

…

Mar

cus

etal

,108

2007

,3-

grou

pRC

T/12

mo

(N�

249)

83.7

%fe

mal

e,m

ean

age�

44.5

�9.

3y,

BMI2

9.4.

Rete

ntio

n:87

.1%

.

Tailo

red

Inte

rnet

:M

otiv

atio

nally

tailo

red

Inte

rnet

mat

eria

ls.

Tailo

red

prin

t:M

otiv

atio

nally

tailo

red

prin

tm

ater

ials

.Re

sear

cher

-sel

ecte

dW

ebsi

tes:

avai

labl

eto

the

publ

ic.

…PA

(min

):NS

Dam

ong

3gr

oups

;w

ithin

grou

pin

crea

seat

6m

o(5

.2%

),12

mo

(5.9

%).

……

(Con

tinue

d)

Artinian et al Promoting Physical Activity and Dietary Changes 413

Tabl

e2.

Cont

inue

d

Refe

renc

e(s)

,Ye

ar,

Stud

yDe

sign

/Du

ratio

n(N

)Po

pula

tion/

Sam

ple

Inte

rven

tion

Outc

omes

Calo

ries/

Fat/F

ruits

and

Vege

tabl

es/F

iber

/Sod

ium

PAW

eigh

tBP

/Cho

lest

erol

/Glu

cose

/He

mog

lobi

nA1

c

Napo

litan

oet

al,34

2003

,2-

grou

pRC

T(N

�65

)

86%

wom

en,

mea

nag

e42

.8y,

91%

whi

te,

55%

�$5

000

0in

com

e/y,

BMI

26.4

.88

%re

tent

ion

3m

o.

C:Re

ceiv

edIa

fter

3-m

ow

ait.

I:Re

ceiv

edac

cess

toW

ebsi

tefo

r3

mo

alon

gw

ithw

eekl

yE-

mai

ltip

shee

ts.

Web

site

base

don

SCT,

targ

eted

stag

esof

mot

ivat

iona

lrea

dine

ss,

and

prov

ided

PAin

form

atio

nto

help

reac

hgo

al(e

g,us

eof

soci

alsu

ppor

t,re

war

ds,

plan

ning

inac

tivity

).

…PA

:At

1m

o,su

bjec

tsin

Igr

oup

had

high

erle

vels

ofm

oder

ate

min

/wk

and

wal

king

min

/wk

vsC

grou

p(P

�0.

05,

�0.

001,

resp

ectiv

ely)

;At

3m

o,on

lyw

alki

ngm

inw

ere

high

erco

mpa

red

with

Cgr

oup

(P�

0.05

).

……

Mic

coet

al,35

2007

,2-

grou

pRC

T/12

mo

(N�

123)

83%

fem

ale,

96%

whi

te,

mea

nag

e46

.8y,

BMI3

1.7,

74%

with

colle

gede

gree

s.

Inte

rnet

:12

-mo

SBT

wei

ght

loss

prog

ram

taug

htth

roug

hse

ries

ofon

line

less

ons.

Subj

ects

met

wee

kly

inon

line

chat

room

s.Ho

mew

ork

assi

gnm

ents

subm

itted

elec

troni

cally

befo

rem

eetin

g.Pr

escr

ibed

diet

of12

00–2

100

cal/d

.Em

phas

ized

diet

abun

dant

inF/

Van

dw

hole

grai

nsan

dm

oder

ate

infa

t,su

gar,

and

salt;

emph

asiz

edex

erci

sing

5–7

days

/wk.

Onlin

em

eetin

gsad

dres

sed

self-

mon

itorin

gan

dse

tting

calo

riean

dPA

goal

s;jo

urna

lspr

ovid

edba

sis

for

feed

back

.In

tern

etpl

usin

-per

son:

Subj

ects

rece

ived

sam

eIn

tern

etpr

ogra

mpl

usm

eton

cea

mon

thas

agr

oup

inpe

rson

.In

-per

son

mee

tings

took

the

plac

eof

onlin

ech

atse

ssio

ns,

led

bydi

ffere

ntfa

cilit

ator

(die

titia

n)th

anon

line

chat

s.

……

Wei

ght

loss

:No

sign

ifica

ntgr

oup�

time

diffe

renc

ein

wei

ght

loss

at6

or12

mo.

Com

plet

ers

lost

mea

n7.

5�6.

4kg

at6

mo

and

6.6�

6.6

kgov

er12

mo.

…

Pint

oet

al,13

220

02,

2-gr

oup

RCT/

6m

o(N

�29

8)

72%

fem

ale,

45%

whi

te,

mea

nag

e45

.9y,

BMI

28–3

0.Re

tent

ion:

TLC-

PA75

%,

TLC-

Eat

89%

.

Tele

phon

e-lin

ked

com

mun

icat

ion

(TLC

)-Ea

t:Pr

omot

edhe

alth

yea

ting,

com

paris

ongr

oup.

TLC-

PA:

Prom

oted

regu

lar

mod

erat

ein

tens

ity(M

I)PA

;TL

Cco

mpu

ter

tech

nolo

gy,

and

digi

tized

hum

ansp

eech

toco

nver

seth

roug

hto

tally

auto

mat

edte

leph

one

conv

ersa

tions

.

NSD

Ener

gyex

pend

iture

:TL

C-E

2.0

vsTL

C-PA

2.3

kcal

/kg/

dat

3m

o,P�

0.02

;ES

�0.

23;

NSD

at6

mo,

ES�

0.02

.

……

Tate

etal

,3620

03,

2-gr

oup

RCT/

1y

(N�

92)

90%

fem

ale,

89%

whi

te,

BMI3

3.Re

tent

ion:

85%

.

Alls

ubje

cts

atte

nded

grou

pse

ssio

n:or

ient

edto

Inte

rnet

;in

stru

cted

onca

lorie

,fa

tre

stric

tion,

PAgo

als;

how

tose

lf-m

onito

r.Ba

sic

Inte

rnet

(BI):

Web

site

tuto

rialo

nw

eigh

tlo

ss,

wee

kly

tipan

dlin

k,di

rect

ory

ofIn

tern

etre

sour

ces,

wee

kly

E-m

ailr

emin

der

tosu

bmit

wei

ght

and

give

nw

eigh

tlo

ssin

fo.

Inte

rnet

wei

ght

loss

prog

ram

�be

havi

oral

E-co

unse

ling

(I�Be

):E-

mai

lco

mm

unic

atio

nw

ithco

unse

lor,

subm

itca

lorie

/fat

inta

ke,

PAon

Web

-bas

eddi

ary

daily

for

1m

o,da

ilyor

wee

kly

for

11m

o;w

eekl

yco

unse

lor

E-m

ailg

ave

feed

back

.

Fat

(%kc

al):

�1%

inBI

grou

pvs

�4%

inI�

Be,

P�0.

06.

Incr

ease

sin

ener

gyex

pend

iture

:�

63in

BIvs

�34

2kc

alin

I�Be

,P�

0.26

.

Wei

ght

loss

:BI

�2.

0kg

vs�

4.4

kgin

I�Be

,P�

0.04

;ES

�0.

21.

…

Tate

etal

,5720

06,

3-gr

oup

RCT/

6m

o(N

�19

2)

�80

%,

�90

%w

hite

,BM

I33.

Rete

ntio

n:82

%at

3m

o,80

%at

6m

o.

Alls

ubje

cts

rece

ived

1gr

oup

sess

ion,

mea

lrep

lace

men

tco

upon

s,ac

cess

toan

inte

ract

ive

Web

site

.No

coun

selin

g(N

C)Co

mpu

ter-

auto

mat

edfe

edba

ck(A

F):

Acce

ssto

elec

troni

cdi

ary

for

self-

mon

itorin

gfo

ods,

PA,

wei

ght;

mes

sage

boar

d;w

eekl

y:E-

mai

lre

min

der

tose

lf-m

onito

r,be

havi

oral

less

on,

and

feed

back

from

prep

rogr

amm

edco

mpu

ter.

Hum

anE-

mai

lCou

nsel

ing

(HC)

:AF

exce

ptfe

edba

ckde

liver

edvi

aE-

mai

lfro

mhu

man

wei

ght

loss

coun

selo

r.

Kcal

:NS

DFa

tin

take

(%/d

):NC

37.2

vsAF

34.0

vsHC

33.1

%/d

,P�

0.00

4.

NSD

Wei

ght

loss

:NC

�2.

6vs

AF�

4.9

vsHC

�7.

2kg

,P�

0.00

1;ES

�0.

29.

…

(Con

tinue

d)

414 Circulation July 27, 2010

Tabl

e2.

Cont

inue

d

Refe

renc

e(s)

,Ye

ar,

Stud

yDe

sign

/Du

ratio

n(N

)Po

pula

tion/

Sam

ple

Inte

rven

tion

Outc

omes

Calo

ries/

Fat/F

ruits

and

Vege

tabl

es/F

iber

/Sod

ium

PAW

eigh

tBP

/Cho

lest

erol

/Glu

cose

/He

mog

lobi

nA1

c

Wyl

ie-R

oset

tet

al,37

2001

,3-

grou

pRC

T/12

mo

(N�

588

from

HMO)

82%

fem

ale,

mea

nag

e52

y,83

%w

hite

,84%

�1

yof

colle

ge,m

ean

BMI3

5.6.

Rete

ntio

n:81

%.

3in

crem

enta

llev

els

ofw

eigh

tlo

ssin

terv

entio

nin

tens

ity:

(1)

Wor

kboo

kal

one

(W);

(2)

addi

tion

ofco

mpu

teriz

edta

ilorin

gus

ing

on-s

iteco

mpu

ter

scre

ens

with

touc

hscr

een

mon

itors

(W�

C);

(3)

addi

tion

ofbo

thco

mpu

ters

and

staf

fco

nsul

tatio

n(ie

,6

clos

ed-g

roup

sess

ions

and

upto

18te

leph

one

orin

-per

son

cons

ulta

tions

).(W

�C�

S).

All3

inte

rven

tions

used

cogn

itive

beha

vior

alap

proa

chfo

rta

ilorin

ggo

als

and

prin

cipl

esof

trans

theo

retic

alm

odel

ofbe

havi

oral

chan

ge.

Mea

nen

ergy

inta

kean

dpe

rcen

ten

ergy

from

fat

decr

ease

dfro

mba

selin

ein

all3

grou

ps(P

�0.

01).

NSD

inm

ean

nutri

ent

inta

keby

grou

p.

Allg

roup

sre

porte

da

mea

nin

crea

sein

wal

king

time

and

num

ber

ofbl

ocks

wal

ked

each

day

(P�

0.01

).NS

Dby

inte

rven

tion

grou

p.

Allg

roup

slo

stw

eigh

t.W

�C�

Slo

stsi

gnifi

cant

lym

ore

wei

ght

than

Won

ly,

P�0.

02.

W�

Cdi

dno

tlo

sew

assi

gnifi

cant

lygr

eate

rw

eigh

tth

anW

only

.

…

Mul

ticom

pone

ntin

terv

entio

nde

liver

yst

rate

gies

Care

lset

al,15

2007

,RC

T/6

mo

(N�

55)

87%

wom

en,o

bese

adul

ts,9

4%w

hite

,BM

Inot

prov

ided

.Re

tent

ion:7

9–81

%.

Beha

vior

wei

ght

loss

prog

ram

(BW

LP):

20se

ssio

nsba

sed

onLE

ARN

prog

ram

.BW

LP�

step

ped

care

(SC)

:In

divi

dual

sin

the

BWLP

�SC

grou

pw

hodi

dno

tm

eet

wei

ght

loss

goal

rece

ived

mot

ivat

iona

lint

ervi

ewin

gst

rate

gies

(MI).

Tota

lcal

orie

s:BW

LP�

380

kcal

vsBW

LP�

SC�

358

kcal

,ES

�0.

11(P

valu

esno

tre

porte

d).

VO2

BWLP

�2.

3vs

BWLP

�SC

�1.

7,ES

�0.

12.

Wei

ght

loss

:BW

LP�

2.1

vsBW

LP�

SC�

4.5,

ES�

0.84

.…

Cook

etal

,221

2007

,lo

ng-t

erm

follo

w-u

p10

–15

yaf

ter

TOHP

Iand

TOHP

IItri

als

(N�

744

inTO

HPI;

N�23

82TO

PHII)

Acro

ssbo

thtri

als:

68.5

%m

en,

�78

%w

hite

,�

17%

blac

k,m

ean

age

43.3

y,m

ean

BMI�

29.

TOHP

trial

:Te

sted

nonp

harm

acol

ogic

alin

terv

entio

ns(ie

,w

eigh

tlo

ss,

Na�

redu

ctio

n,st

ress

man

agem

ent,

and

nutri

tiona

lsup

plem

ents

)in

redu

cing

BPin

subj

ects

with

high

norm

alBP

.Of

2182

TOHP

Isub

ject

s,32

7w

ere

rand

omiz

edto

Na�

redu

ctio

nan

d41

7w

ere

assi

gned

toUC

.In

divi

dual

and

wee

kly

grou

pse

ssio

nsof

fere

dfo

r3

mo;

lifes

tyle

inte

rven

tions

wer

eof

fere

dfo

r18

mo.

Com

pare

dw

ithUC

,Na

�an

dBP

sign

ifica

ntly

decr

ease

d.TO

PHII:

Test

edth

eef

fect

sof

wei

ght

loss

and

Na�

onin

cide

nthy

perte

nsio

nan

dBP

over

3–4

year

s.2�

2fa

ctor

iald

esig

n.Th

eNa

�re

duct

ion

only

grou

pha

dsi

gnifi

cant

lylo

wer

Na�

excr

etio

nw

ithco

rres

pond

ing

sign

ifica

ntde

crea

sein

SBP.

……

…CV

D:Ri

skof

aCV

Dev

ent

(MI,

stro

ke,

CVre

vasc

ular

izat

ion

orCV

deat

h)w

as25

%lo

wer

amon

gth

ose

inin

terv

entio

ngr

oup,

adju

sted

for

trial

,cl

inic

,ag

e,se

x,an

dra

ce;

risk

was

30%

low

eraf

ter

furth

erad

just

men

tfo

rba

selin

eNa

�ex

cret

ion

and

wei

ght.

Diab

etes

Prev

entio

nPr

ogra

mRe

sear

chGr

oup,

38,2

2820

04,

3-gr

oup

RCT/

aver

age

2.8

y(N

�32

34)

ILIg

roup

was

68%

fem

ale,

46.3

%m

inor

ity,

BMI3

4.Re

tent

ion:

92.5

%

Stan

dard

:st

anda

rdlif

esty

lepl

aceb

ogr

oup

Met

form

in:

850

mg

twic

eda

ily.

Inte

nsiv

eLi

fest

yle

Inte

rven

tion

(ILI):

Mai

ngo

al:

lose

7%of

base

line

wei

ght

and

achi

eve

150

min

/wk

ofPA

;in

divi

dual

case

man

ager

for

full

time

ofst

udy—

16se

ssio

nsin

core

curr

icul

umco

vere

dba

sic

skill

sre

late

dto

nutri

tion,

exer

cise

,an

dbe

havi

orch

ange

.Di

et�

25%

fat�

calo

riere

stric

tion.

Self-

mon

itore

dm

inof

PAan

dfa

tg

cons

umed

ever

yda

ydu

ring

core

curr

icul

um,

then

1w

k/m

ore

mai

nder

oftri

al.

Note

:In

cide

nce

ofdi

abet

esre

duce

dsi

gnifi

cant

lygr

eate

rin

the

ILIg

roup

than

inth

est

anda

rdan

dm

etfo

rmin

grou

ps.

For

ILL

grou

p:Kc

al/d

:�

452

at1

yTo

talf

at/d

(g):

�30

.3at

1y

%of

calf

rom

fat:

�6.

6%at

1y.

PA(M

ETS)

:�

6.6

at1

y,�

4.3

MET

Sat

3y.

Wei

ght

loss

:�

4.2

kgin

ILI

grou

pvs

0.8

kgin

stan

dard

grou

p,P�

0.05

at12

mo.

InIL

L,�

4.1

kgat

3y.

…

Glas

gow

etal

,39

1997

,2-

grou

pRC

T/12

mo

(N�

206)

Adul

tsw

ithDM

,�60

%fe

male

,mea

nag

e62

y,77

%ov

erw

eight

orob

ese,

race

not

repo

rted.

Rete

ntion

:In

terv

entio

n:83

.3%

;UC

:84.

7%.

UC:

Quar

terly

med

ical

care

and

F/U

ofris

kfa

ctor

s�to

uch-

scre

enco

mpu

ter

asse

ssm

ent

inm

edic

alof

fice.

Brie

fIn

terv

entio

n(B

I):Si

ngle

sess

ion,

touc

h-sc

reen

com

pute

r–as

sist

edas

sess

men

t,im

med

iate

feed

back

onke

yba

rrie

rsto

diet

ary

self-

man

agem

ent,

goal

setti

ng,

and

prob

lem

-sol

ving

coun

selin

g;ad

ditio

nal

vide

oin

terv

entio

nba

sed

onse

lf-ef

ficac

ysc

ore

(�85

vs�

85).

Tele

phon

eca

lls/v

ideo

tape

s1

and

3w

ks;

inte

rven

tion

repe

ated

at3

mo;

tele

phon

eca

llat

6m

o,DM

book

at12

mo.

Kcal

:UC

1659

vsBI

1547

kcal

,P�

0.05

;ES

�0.

14Fa

t(%

):UC

32.0

%vs

30.5

%,

P�0.

023;

ES�

0.16

.

…BM

I:NS

D.Ch

oles

tero

l:UC

226

vsBI

208,

P�0.

002

HbA 1

c,NS

D.

(Con

tinue

d)

Artinian et al Promoting Physical Activity and Dietary Changes 415

Tabl

e2.

Cont

inue

d

Refe

renc

e(s)

,Ye

ar,

Stud

yDe

sign

/Du

ratio

n(N

)Po

pula

tion/

Sam

ple

Inte

rven

tion

Outc

omes

Calo

ries/

Fat/F

ruits

and

Vege

tabl

es/F

iber

/Sod

ium

PAW

eigh

tBP

/Cho

lest

erol

/Glu

cose

/He

mog

lobi

nA1

c

Glas

gow

,8020

00,

2�2

Fact

oria

lRC

T/6

mo

(N�

320)

Adul

tsw

ithty

pe2

DM,m

ean

age

59y,

BMIn

otre

porte

d.Re

tent

ion:

84%

–94

%fo

r4

grou

ps.

Subj

ects

rece

ived

Basi

cIn

terv

entio

n(B

I):he

alth

coun

selo

rm

eetin

g,di

etar

ygo

als

set

with

aid

ofto

uch-

scre

enco

mpu

ter,

feed

back

ondi

etar

ypa

ttern

.Ta

ilore

ddi

etar

yfa

tre

duct

ion

goal

.4

grou

ps:

(1)

BI;

(2)

BI�

TF(3

–4

tele

phon

efo

llow

-up

calls

/6m

ofo

ron

goin

gsu

ppor

t,re

info

rcem

ent,

and

prob

lem

-sol

ving

);(3

)BI

�Co

mm

unity

Reso

urce

s(C

R)En

hanc

emen

t;(4

)Co

mbi

ned

Cond

ition

s.CR

Enha

ncem

ent:

bind

erof

reso

urce

s,4

new

slet

ters

,go

alse

tting

,an

dFF

Qco

mpl

eted

/giv

enta

ilore

dfe

edba

ck.

Fat:

NSD;

ES�

0.19

.Fa

t/fib

erbe

havi

ors:

TFgr

oups

bette

r,P�

0.01

7.

…NS

DCh

oles

tero

l:CR

�ph

ase

P�0.

010

HbA 1

c,NS

D

How

ard

etal

,58

2006

,W

HI:

Diet

ary

Mod

ifica

tion

Tria

l2-

grou

pRC

T/7.

5y

(N�

4883

5)

Post

men

opau

sal

wom

en,

81%

whi

te,

BMI2

9.Re

tent

ion:

96%

.

C:Us

uald

iet,

rece

ived

diet

-rel

ated

educ

atio

nm

ater

ials

(Die

tary

Guid

elin

esfo

rAm

eric

ans)

I:Gr

oup

(18

sess

ions

infir

stye

ar,

4/y

afte

rwar

d)an

din

divi

dual

sess

ions

topr

omot

ede

crea

sein

fat

inta

ke,

incr

ease

inF/

Van

dgr

ain

inta

ke;

mai

ntai

nus

uale

nerg

yin

take

(no

wei

ght

loss

orca

lorie

rest

rictio

ngo

als)

.Th

ree

indi

vidu

alse

ssio

nsth

atus

edre

flect

ive

liste

ning

.Se

lf-m

onito

red

diet

ary

fat,

F/V,

grai

nin

take

thro

ugho

utst

udy.

Kcal

:C

vsI:

�24

0.8

vs�

361.

4,P�

0.00

1;ES

�0.

02%

fat:

�0.

6vs

�8.

8%P�

0.00

1F/

V:0.

2vs

1.4

serv

ings

,P�

0.00

1Fi

ber:

�0.

2vs

2.2

,P�

0.00

1.

PA(M

ETS)

:Co

nvs

I0.9

vs1.

1M

ETs,

P�0.

07.

Wei

ght

chan

gedi

ffere

nce

Can

dI

grou

psat

12m

o,1.

9kg

,P�

0.00

1;at

7y,

0.4

kg,

P�0.

01.

…

Look

AHEA

DRe

sear

chGr

oup,

111

2007

,2-

grou

pRC

T/12

mo

(N�

5145

)

Adul

tsw

ithT2

DM,

59%

fem

ale,

63%

whi

te,m

ean

age

59y,

BMI3

5–36

.Re

tent

ion

at1

y:�

96%

Diab

etes

supp

ort

and

educ

atio

nco

nditi

on(D

SE):

4se

ssio

nson

topi

csre

late

dto

diet

and

PA,

noco

unse

ling,

not

wei

ghed

.In

tens

ive

lifes

tyle

inte

rven

tion

(ILI):

Grou

pan

din

divi

dual

mee

tings

toac

hiev

e/m

aint

ain

7%w

eigh

tlo

ssvi

ade

crea

sed

calo

ricin

take

(30%

fat)

and

porti

on-c

ontro

lled

diet

s;in

crea

sed

PA(1

75m

in/w

k);

3gr

oup

mee

tings

�1

indi

vidu

alm

eetin

gm

onth

lydu

ring

mo

1–6,

2gr

oup

mee

tings

�1

indi

vidu

alm

eetin

gm

onth

lyfo

r7–

12m

o.

…Ca

rdio

resp

irato

ryfit

ness

:Fi

tnes

sin

crea

ses

10.8

%in

DSE

vs15

.9%

inIL

I,P�

0.00

1.

Wei

ght

loss

:0.

7%vs

8.6%

ofin

itial

body

wei

ght,

P�0.

0001

.

DSE

vsIL

I:SB

P�

2.8

vs�

6.8,

P�0.

001;

DBP

�1.

8vs

�3.

0,P�

0.00

1;HD

L�

1.4

vs�

3.4,

P�0.

001;

gluc

ose

�7.

2vs

21.5

,P�

0.00

1.

Perr

yet

al,40

2007

,2-

grou

pRC

T/12

wk

(N�

46)

100%

rura

lwom

en,

95%

whi

te,

mea

nag

e45

y,m

ean

educ

atio

n�15

y.

HTH:

Indi

vidu

al�

grou

pco

mpo

nent

s.In

divi

dual

com

pone

ntin

clud

edm

otiv

atio

nali

nter

view

ing

for

30m

inat

base

line

follo

wed

byw

eekl

y10

-min

boos

ter

calls

.W

omen

aske

dto

set

goal

san

dm

onito

rpr

ogre

ssan

dre

ceiv

edin

divi

dual

ized

exer

cise

pres

crip

tion.

Grou

pco

mpo

nent

incl

uded

anu

rse

led

1-h

wee

kly

grou

pw

alk

topr

omot

esu

ppor

tan

dse

lf-ef

ficac

y.Co

mpa

rison

:Su

bjec

tsre

ceiv

eda

brie

f10

-min

indi

vidu

alpr

ivat

ead

vice

sess

ion,

am

onth

ly5-

min

rein

forc

emen

tca

ll,an

indi

vidu

aliz

edex

erci

sepr

escr

iptio

n,an

da

logb

ook

tore

cord

wal

king

.

…Ca

rdio

resp

irato

ryfit

ness

per

dist

ance

wal

ked

in12

-min

wal

kte

st:

Wom

enin

HTH

had

grea

ter

impr

ovem

ent

infit

ness

,P�

0.05

7vs

com

paris

ongr

oup.

……

Stev

ens

etal

,41

2001

,4-

grou

pRC

T(T

OHP

II)/3

6m

o(N

�11

91)

66%

male

,mea

nag

e43

year

s,79

%w

hite

;BM

I31.

Rete

ntion

:92%

and

93%

forw

eight

loss,

89%

and

86%

forB

Pm

easu

re.

UC:

Not

desc

ribed

.W

eigh

tlo

ssin

terv

entio

n(W

LI):

Indi

vidu

alco

unse

ling

follo

wed

by14

wee

kly

grou

pm

eetin

gs;

ther

eafte

r,6

biw

eekl

ygr

oup

mee

tings

.Af

ter

18m

o,op

tions

incl

uded

indi

vidu

alor

grou

pse

ssio

nson

sele

cted

wei

ght-

loss

topi

cs.

Focu

son

beha

vior

alse

lf-m

anag

emen

t,so

cial

supp

ort;

incl

uded

self-

mon

itorin

g,go

alse

tting

,de

velo

ping

actio

npl

ans,

and

prob

lem

solv

ing.

Wei

ght

loss

goal

of�

4.5

kg,

PA30

–45

min

utes

,4–

5/w

k.

……

Wei

ght

loss

:UC

vsW

LI:

�0.

1vs

�4.

4,0.

7vs

�2.

0,an

d1.

8vs

�0.

2kg

at6,

18,

36m

o,P�

001;

ES�

0.10

.

Diffe

renc

ein

scor

es:

SBP

�3.

7,�

1.8,

�1.

3m

mHg

at6,

18,

36m

o,P�

0.01

.DB

P�

2.7,

�3.

5,�

2.0

mm

Hgat

6,18

,36

mo.

P�0.

001–

0.05

;P�

0.00

1–P�

0.05

.

Writ

ing

Grou

pfo

rAc

tivity

Coun

selin

gTr

ial,13

520

01,

RCT/

24m

o(N

�87

4)

55%

mal

es,m

ean

age

51y,

�60

%w

hite

;BM

I29–

30.

Rete

ntio

n:91

.4%

com

plet

edPA

,77

.6%

VO2

max

.

Advi

ce(A

D):

Incl

udes

phys

icia

nad

vice

and

writ

ten

educ

atio

nalm

ater

ials

(reco

mm

ende

dca

re).

Assi

stan

ce(A

S):

Com

pone

nts

ofAD

grou

p�in

tera

ctiv

em

aila

ndbe

havi

oral

coun

selin

gat

phys

icia

nvi

sits

.Co

unse

ling

(Cou

n):

Allo

fAD

and

ASco

mpo

nent

s�re

gula

rte

leph

one

coun

selin

gan

dbe

havi

oral

clas

ses.

…VO

2m

ax:

Sign

ifica

ntly

high

erin

ASth

anAD

grou

p(8

0.8

mL)

,hi

gher

inCo

unth

anin

ADgr

oup

(73.

9m

L);

NSD

inm

en;

ES�

0.07

–0.0

8.

……

RCT

indi

cate

sra

ndom

ized

cont

rolle

dtri

al;I

,int

erve

ntio

ngr

oup;

BP,b

lood

pres

sure

;PCP

,prim

ary

care

prov

ider

;C,c

ontro

lorc

ompa

rison

grou

p;SB

P,sy

stol

icbl

ood

pres

sure

;DBP

,dia

stol

icbl

ood

pres

sure

;NSD

,no

sign

ifica

ntdi

ffere

nce;

ES,e

ffect

size

;LDL

-C,l

ow-d

ensi

tylip

opro

tein

chol

este

rol;

F/U,

follo

w-u

p;DM

,dia

bete

sm

ellit

us;U

C,us

ualc

are;

MET

s,m

etab

olic

equi

vale

nts;

HS,h

igh

scho

ol;F

/V,f

ruits

and

vege

tabl

es;H

DL,h

igh-

dens

itylip

opro

tein

;FF

Q,Fo

odFr

eque

ncy

Ques

tionn

aire

;SC

T,so

cial

cogn

itive

theo

ry;

HMO,

heal

thm

aint

enan

ceor

gani

zatio

n;CV

D,ca

rdio

vasc

ular

dise

ase;

and

Hb,

hem

oglo

bin.

416 Circulation July 27, 2010

Tabl

e3.

RCTs

ofIn

terv

entio

nsto

Prom

ote

PAan

dDi

etar

yLi

fest

yle

Chan

ge:M

inor

itySa

mpl

es

Refe

renc

e(s)

,Ye

ar,

Stud

yDe

sign

/Du

ratio

n(N

)Po

pula

tion/

Sam

ple

Inte

rven

tion

Outc

omes

Calo

ries/

Fat/F

ruits

and

Vege

tabl

es/F

iber

/Sod

ium

PAW

eigh

tBP

/Cho

lest

erol

/Glu

cose

/He

mog

lobi

nA1

c

Grou

p-ba

sed

inte

rven

tion

deliv

ery

stra

tegi

es

Elde

ret

al,11

0

1998

,2-

grou

pcl

uste

rra

ndom

ized

para

llelg

roup

trial

/3-m

opo

stte

stan

d6

mo

(N�

408)

Adul

tsen

rolle

din

Engl

ish

asse

cond

lang

uage

clas

ses,

mea

nag

e28

.7y,

�50

%fe

mal

e,in

US�

3y.

87%

Hisp

anic

,66

%m

onth

lyin

com

e�

$109

9.

Nutri

tion

Hear

t-He

alth

Educ

atio

n:Fi

ve3-

hgr

oup

clas

ses

onnu

tritio

n/he

art

heal

th;

cultu

rally

sens

itive

clas

ses

cond

ucte

din

Engl

ish

and

Span

ish.

Stre

ss-m

anag

emen

tEd

ucat

ion:

Five

3-h

grou

pcl

asse

son

stre

ssm

anag

emen

t.

……

Wei

ght

loss

:Nu

tritio

ngr

oup:

Nolo

ss,

gain

of2.

5lb

at6

mo

vs0.

66lb

gain

inSt

ress

grou

p.14

1.65

lb(n

obe

twee

n-gr

oup

diffe

renc

es).

Tota

lcho

leste

rol,

mg/

dL:N

utrit

iongr

oup

178.

94at

base

line,

169.

88at

6m

o.St

ress

grou

p17

7.03

atba

selin

e,16

6.18

at6

mo.

With

ingr

oup

diffe

renc

e,P�

0.01

.NSD

betw

een

grou

ps.

HDL

chole

ster

ol,m

g/dL

:NSD

with

inor

betw

een

grou

ps.

BPm

mHg

:sig

nific

antw

ithin

-gro

upch

ange

s,P�

0.00

1.NS

Dbe

twee

ngr

oups

.

Hartm

anet

al,96

1997

,qua

si-ex

perim

enta

lde

sign/

8w

ks(N

�20

4)

Low

liter

acy

adul

tsnu

tritio

ned

ucat

ion

prog

ram

for

the

low

inco

me.

94%

fem

ale,

32%

blac

k,57

%in

com

e�

$10

000/

y.

I:Re

ceiv

edlo

w-f

atnu

tritio

ned

ucat

ion

“Hel

pYo

urse

lfto

Heal

th”

infu

nan

den

terta

inin

gfo

rmat

;10

sess

ions

onlo

w-f

atnu

tritio

n,ta

ught

byNu

tritio

nEd

ucat

ion

Assi

stan

tsw

holiv

edin

the

com

mun

ity.

Grou

psm

etat

com

mun

itysi

tes;

liter

acy

leve

ladd

ress

ed.

C:Re

ceiv

edus

ualE

xpan

ded

Food

and

Nutri

tion

Educ

atio

nPr

ogra

m—

food

budg

etin

g,fo

odsa

fety

,an

dhe

alth

yea

ting.

Calo

ries:

per

24-h

reca

ll.En

ergy

/kca

ls:

NSD

with

inor

betw

een

grou

ps.

Tota

lfat

(kca

ls):

NSD

with

inor

betw

een

grou

ps.

……

Tota

lcho

lest

erol

(mg/

dL),

treat

men

tgr

oup:

NSD

with

inor

betw

een

grou

ps.

How

ard-

Pitn

eyet

al,54

2-gr

oup

clus

ter

RCT/

�5

mo

(N�

351)

Adul

tsre

crui

ted

from

adul

ted

ucat

ion

clas

ses.

59%

Hisp

anic

,85

%w

omen

,66

%ha

dre

adin

gle

vela

tsi

xth

grad

ele

velo

rbe

low

,65

%fa

mily

inco

me

�$1

000

0/y.

I:A

diet

ary

fat

curr

icul

umof

fere

dov

er20

mo;

2pa

rts,

6w

ksin

clas

sroo

mfo

llow

edby

a12

-wk

mai

nten

ance

inte

rven

tion;

taug

htby

nutri

tion

educ

ator

s;si

x90

-min

,w

hich

wer

ein

tera

ctiv

ew

ithfe

ww

ritte

nm

ater

ials

,pl

ussk

illbu

ildin

g,fo

odta

stin

gs,

and

dem

onst

ratio

nsof

low

-fat

goal

sse

tby

parti

cipa

nts.

12-w

km

aint

enan

cein

terv

entio

n(ie

,co

ntac

tev

ery

2w

ksby

tele

phon

eor

mai

lfor

6co

ntac

ts(to

prov

ide

supp

ort

and

enco

urag

emen

t);m

etho

dsan

dm

ater

ials

tailo

red

for

adul

tw

ithlo

wlit

erac

y.C:

Gene

raln

utrit

ion

clas

ses

taug

htby

para

prof

essi

onal

educ

atio

n;de

sign

edto

impr

ove

know

ledg

ean

dnu

tritio

nch

oice

s.Ad

dres

sed

food

pyra

mid

,fo

odsa

fety

and

mea

lpla

nnin

g.

Tota

lfat

:pe

rFF

Q%

cals

from

fat,

chan

gefro

mba

selin

e,I�

37.1

%–3

3.2%

;vs

C�36

.4%

–35.

2%.

Sign

ifica

ntw

ithin

-gro

updi

ffere

nce,

for

I:P�

0.01

.No

betw

een-

grou

pdi

ffere

nces

.To

talf

at(g

/d):

NSD

with

inor

betw

een

grou

ps.

…BM

I:ch

ange

from

base

line.

NSD

with

ingr

oup

orbe

twee

ngr

oups

.

Chol

este

rol(

mg/

dL):

chan

gefro

mba

selin

e.NS

Dw

ithin

grou

por

betw

een

grou

ps.

Kum

anyi

kaet

al,42

2005

,2-

phas

etri

al,

phas

e1

all

rece

ived

grou

pcl

asse

s;ph

ase

II2-

grou

pRC

T/12

mo

(N�

87co

mpl

eted

phas

eII)

100%

blac

k,90

%fe

mal

e,m

ean

age

�44

.4y,

�67

%ed

ucat

ion

�12

y,m

ean

BMI3

7.5.

Phas

eI—

Grou

pco

unse

ling

prog

ram

(HEL

P):

Alli

nter

este

dpa

rtici

pant

sen

rolle

din

10w

eekl

ygr

oup

wei

ght

loss

clas

ses;

nosp

ecifi

cdi

etor

calo

ricin

take

spec

ified

;su

bjec

tsen

cour

aged

tose

tpe

rson

algo

als

and

tose

lf-m

onito

rdi

et;

advi

ceto

incr

ease

PAw

asin

divi

dual

lyta

ilore

dto

abili

tyan

dpr

efer

ence

.3

mo

afte

ren

rollm

ent

subj

ects

rand

omiz

edto

phas

eII

inte

rven

tions

:Cl

asse

s:HE

LPcl

asse

s�gr

oup

coun

selin

gof

fere

dbi

wee

kly,

then

mon

thly

vsw

eekl

y.En

hanc

edse

lf-he

lp:

Staf

ffa

cilit

ated

self-

help

;su

bjec

tsre

ceiv

eda

pers

onal

ized

cale

ndar

,a

pack

ets

desc

ribin

glo

calr

esou

rces

,a

pers

onal

diar

y,a

pedo

met

er,

and

adho

cte

leph

one

supp

ort.

UC:

Nofu

rther

coun

selin

gou

tsid

ebr

ief

coun

selin

gat

sem

iann

ualc

linic

visi

ts.

……

Wei

ght

loss

(kg)

:�

1.2�

5.2

over

entir

est

udy

perio

d,P�

0.05

.Ne

ither

HELP

clas

ses

nor

self-

help

was

supe

rior

toUC

durin

gph

ase

II.

SBP

(mm

Hg):

�6.

5�11

over

entir

est

udy

perio

d,P�

0.01

;DB

P(m

mHg

):�

4.9�

6.8.

Nosi

gnifi

cant

chan

ges

into

tal

chol

este

rol,

trigl

ycer

ides

,or

bloo

dgl

ucos

e.

(Con

tinue

d)

Artinian et al Promoting Physical Activity and Dietary Changes 417

Tabl

e3.

Cont

inue

d

Refe

renc

e(s)

,Ye

ar,

Stud

yDe

sign

/Du

ratio

n(N

)Po

pula

tion/

Sam

ple

Inte

rven

tion

Outc

omes

Calo

ries/

Fat/F

ruits

and

Vege

tabl

es/F

iber

/Sod

ium

PAW

eigh

tBP

/Cho

lest

erol

/Glu

cose

/He

mog

lobi

nA1

c

McN

abb

etal

,43

1997

,2-

grou

pRC

T/1

wk

afte

rI

finis

hed

(N�

39)

Wom

enre

crui

ted

from

3ur

ban

blac

kch

urch

es.

Mea

nag

e56

y,BM

I�30

,13

%�

HSed

ucat

ion,

appr

oxim

atel

y54

%em

ploy

ed

I:PA

THW

AYS

prog

ram

:14

-wk

smal

llay

-led

cultu

rally

sens

itive

grou

pse

ssio

nsat

chur

chon

diet

that

incl

uded

goal

setti

ng,

prob

lem

solv

ing,

and

inst

ruct

ions

toen

gage

inre

crea

tiona

lwal

king

adm

inis

tere

dby

lay

faci

litat

ors

atth

ech

urch

es;

incl

uded

use

ofet

hnic

food

s.C:

Wai

t-lis

tco

ntro

l.

……

Wei

ght

loss

(lb):

�10

.0�

10.2

8vs

C�

1.9�

4.25

,P�

0.00

01.

BMI(

kg/m

2 ):Ig

roup

�1.

4�1.

61vs

Cgr

oup

0.6�

0.73

,P�

0.00

01,

ES�

0.65

.

…

Indi

vidu

al-b

ased

inte

rven

tion

deliv

ery

stra

tegi

es

Ahlu

wal

iaet

al,93

2007

,cl

uste

rra

ndom

ized

trial

of20

publ

icho

usin

gde

velo

pmen

ts/6

mo

(N�

173)

100%

smok

ers,

mea

nag

e45

.5y,

81.3

%bl

ack,

�38

%HS

educ

atio

n,42

%un

empl

oyed

,�

73%

mon

thly

inco

me

�$8

00.

Both

arm

sre

ceiv

ed5

sess

ions

ofm

otiv

atio

nali

nter

view

ing

coun

selin

gfo

rF/

Vor

smok

ing

cess

atio

n.Se

lf-ef

ficac

yan

dba

lanc

ing

pros

and

cons

ofch

ange

and

2-di

men

sion

alm

odel

ofcu

ltura

lsen

sitiv

itygu

ided

inte

rven

tions

.Fr

uit

and

vege

tabl

ein

terv

entio

n(F

/V):

Rece

ived

aba

gof

fresh

F/Vs

,a

cook

book

ofhe

alth

yre

cipe

s,di

etar

yed

ucat

ion

mat

eria

ls,

and

2vi

deos

onF/

Vs.

Smok

ing

cess

atio

nin

terv

entio

n(S

C):

Rece

ived

an8-

wee

ksu

pply

ofni

cotin

egu

man

din

stru

ctio

nsab

out

quitt

ing.

F/V:

At8

wee

ksan

d6

mo,

the

F/V

grou

pco

nsum

ed1.

58(P

�0.

001)

and

0.78

(P�

0.04

),re

spec

tivel

y,m

ore

F/V

serv

ings

per

day

than

SC.

Com

plet

ing

mor

em

otiv

atio

nali

nter

view

sess

ions

(P�

0.02

)an

dtry

ing

mor

ere

cipe

s(P

�0.

02)

led

tosi

gnifi

cant

lygr

eate

rin

crea

seof

F/Vs

inth

eF/

Vgr

oup.

……

…

Eaki

net

al,44

2007

,2-

grou

pRC

T/6

mo

(N�

200)

Adul

tsw

ith�

1ch

roni

cco

nditi

ons.

Mea

nag

e49

.5y,

75%

Hisp

anic

,�

5y

inUS

,79

%fe

mal

e,�

36%

�$1

000

0/y.

I:Bi

lingu

alhe

alth

educ

ator

prov

ided

2-in

divi

dual

sess

ions

onPA

and

diet

ary

reco

mm

enda

tions

(60–

90m

in)

3m

oap

art

atho

me

orcl

inic

;fe

edba

ckon

base

line

asse

ssm

ent;

parti

cipa

nts

chos

ePA

and

diet

goal

;go

alse

tting

,fe

edba

ckan

dpr

oble

mso

lvin

gpl

usID

ofm

ultil

evel

/co

mm

unity

supp

orts

for

heal

thbe

havi

orch

ange

emph

asiz

ed.

3fo

llow

-up

tele

phon

eca

llsdu

ring

6-m

oin

terv

entio

n;lo

w-li

tera

cyle

tters

rem

inde

dpa

rtici

pant

sof

goal

s,ad

dres

sed

barr

iers

,an

dsu

gges

ted

reso

urce

s;al

lact

iviti

esad

apte

dto

liter

acy

leve

l(vi

sual

aids

)an

dcu

lture

;in

terv

entio

nstra

nsla

ted

into

Span

ish

and

valid

ated

.UC

:Su

bjec

tsw

ere

mai

led

alo

calc

omm

unity

reso

urce

sgu

ide

and

3ne

wsl

ette

rson

finan

cial

man

agem

ent.

Fat/f

iber

inta

kepe

rse

lf-re

port

ques

tionn

aire

:At

6-m

onth

the

Igr

oup

had

sign

ifica

ntly

bette

rFa

t/fib

erin

take

com

pare

dw

ithUC

grou

p,P�

0.05

.

PA:

Chan

gefro

mB

inm

inut

esw

alke

d,NS

Dw

ithin

orbe

twee

ngr

oups

.

……

Elde

ret

al,14

4

2006

,3-

grou

pRC

T/12

mo

(N�

367)

Latin

aw

omen

,m

ean

age

39.7

�9.

9y,

BMI2

8.9–

30.4

.Re

tent

ion

76%

–82%

for

3gr

oups

.

Tailo

red

(T):

12ta

ilore

dpr

int

new

slet

ters

with

hom

ewor

kas

sign

men

tsm

aile

dw

eekl

y.Pr

omot

ora

(P):

Wee

kly

hom

evi

sits

orte

leph

one

calls

byla

yad

viso

rov

er14

wks

�12

tailo

red

new

slet

ters

and

hom

ewor

k.As

sess

men

tat

base

line,

12w

ks,

and

6an

d12

mo.

C:12

off-

the-

shel

fm

ater

ials

mai

led

wee

kly

toho

me.

Kcal

:Pr

omot

ora

1288

.7vs

Tailo

red

1420

.6vs

C14

30.5

;P�

0.01

8at

12w

ks,

NSD

at6

and

12m

o.Fa

t:Pr

omot

ora

43.1

gvs

Tailo

red

49.8

g,C

49.1

g;P�

0.02

8at

12w

ks,

NSD

at6

and

12m

o;ES

�0.

14.

……

…

(Con

tinue

d)

418 Circulation July 27, 2010

Tabl

e3.

Cont

inue

d

Refe

renc

e(s)

,Ye

ar,

Stud

yDe

sign

/Du

ratio

n(N

)Po

pula

tion/

Sam

ple

Inte

rven

tion

Outc

omes

Calo

ries/

Fat/F

ruits

and

Vege

tabl

es/F

iber

/Sod

ium

PAW

eigh

tBP

/Cho

lest

erol

/Glu

cose

/He

mog

lobi

nA1

c

Jaco

bset

al,45

2004

,cl

uste

rra

ndom

ized

trial

of22

heal

thde

partm

ents

/12

mo

(N�

421)

100%

low

-inco

me

fem

ale,

mea

nag

e59

y,51

%�

HSed

ucat

ion,

44%

from

ethn

icm

inor

itygr

oups

.

Alls

ubje

cts

prev

ious

lypa

rtici

pate

din

a1-

ydi

etan

dPA

beha

vior

chan

gepr

ogra

m(p

hase

II):

North

Caro

lina

WIS

EWOM

AN,

inw

hich

heal

thde

partm

ents

wer

era

ndom

ized

toth

een

hanc

edin

terv

entio

nor

the

min

imal

inte

rven

tion.

Inph

ase

III,

ofth

e22

heal

thde

partm

ents

who

had

rece

ived

the

enha

nced

inte

rven

tion

inph

ase

II,11

wer

era

ndom

ized

toM

aint

enan

ceSp

ecia

lInt

erve

ntio

nan

d11

wer

era

ndom

ized

toM

aint

enan

ceUs

ualC

are.

Mai

nten

ance

Spec

ialI

nter

vent

ion

(MSI

):Su

bjec

tsw

ere

mai

led

6bi

mon

thly

com

pute

r-ta

ilore

dhe

alth

mes

sage

san

dre

ceiv

ed2

tele

phon

eca

llsfro

mhe

alth

depa

rtmen

tst

aff.

Inte

rven

tion

mat

eria

lsw

ere

base

don

soci

alco

gniti

veth

eory

,re

laps

epr

even

tion

theo

ry,

and

the

trans

theo

retic

alm

odel

.Ta

ilorin

gw

asac

cord

ing

togo

als,

stag

eof

chan

ge,

know

ledg

e,so

cial

supp

ort

syst

ems,

high

-ris

ksi

tuat

ions

for

rela

pse,

and

perc

eive

dbe

nefit

san

dba

rrie

rs.

Mes

sage

sw

ere

desi

gned

for

low

-lite

rate

and

low

-inco

me.

Mai

nten

ance

Usua

lCar

e(M

UC):

Rece

ived

usua

lfol

low

-up

serv

ices

atth

edi

scre

tion

ofth

ehe

alth

depa

rtmen

ts.

Basi

cnu

tritio

nan

dPA

coun

selin

gpa

mph

lets

wer

eav

aila

ble.

Both

grou

psm

aint

aine

dlo

wre

porte

din

take

leve

lsof

diet

ary

satu

rate

dfa

tan

dch

oles

tero

l.

Both

grou

psm

aint

aine

dlo

wle

vels

ofse

lf-re

porte

dPA

.Su

bjec

tsin

MSI

wer

em

ore

likel

yto

mov

efo

rwar

din

tom

ore

adva

nced

stag

esof

PA,

P�0.

02.

……

Resn

icow

etal

,103

2005

,3-

grou

pcl

uste

rra

ndom

ized

trial

/1y

(N�

906)

Mea

nag

e46

.3y,

76.2

%fe

mal

e,10

0%bl

ack,

60%

inco

me

�$4

000

0/y,

�70

%so

me

colle

ge.

C:St

anda

rdco

mm

erci

alse

lf-he

lpvi

deos

and

broc

hure

sm

atch

edfo

rin

tens

ityan

dty

pew

ithgr

oup

2m

ater

ials

.Cu

ltura

llyta

rget

edse

lf-he

lpnu

tritio

nan

dPA

:Cul

tura

llyta

ilore

dnu

tritio

nvid

eo,c

ookb

ook,

exer

cise

video

,exe

rcise

guid

e,an

dau

dio

cass

ette

.M

otiva

tiona

lInt

ervie

w(M

I)pl

usgr

oup

2in

terv

entio

n:4

MIs

essio

nsde

liver

edby

tele

phon

eat

4,12

,26,

and

40w

ks.T

wo

calls

addr

ess

F/V

and

2ca

llad

dres

sed

PA.S

elf-h

elp

mat

eria

lsre

view

eddu

ring

calls

.

F/V:

MIi

ncre

ased

F&V

inta

keco

mpa

red

with

othe

r2

grou

ps,

P�0.

05.

PA:

Tota

lmin

/wk

ofPA

incr

ease

din

Cultu

rala

ndM

Igr

oups

com

pare

dw

ithC,

P�0.

05.

NSD

betw

een

cultu

rean

dM

I.

……

Mul

ticom

pone

ntin

terv

entio

nde

liver

yst

rate

gies

Albr

ight

etal

,46

2005

,2-

grou

pRC

T/10

wks

,6

mo,

and

1y

(N�

72)

Sede

ntar

ylo

w-in

com

ew

omen

recr

uite

dfro

mad

ult

educ

atio

nsi

tes,

mea

nag

e32

y,73

%Hi

span

ic,

�70

%in

com

e�

$20

000/

y.

Allr

ecei

ved

8w

eekl

y1-

hPA

skill

-bui

ldin

gcl

asse

sta

ught

byet

hnic

ally

mat

ched

educ

ator

s;in

clud

edsm

allg

roup

disc

ussi

ons

and

Q&A;

Goal

30m

inof

mod

erat

ePA

5da

ys/w

k.Af

ter

clas

ses,

subj

ects

rand

omiz

edto

:Ho

me-

base

dte

leph

one�

mai

lsup

port

(P�

MS)

:W

eekl

yte

leph

one

coun

selin

gfo

rfir

st4

wks

,bi

wee

kly

for

8w

ks,

then

mon

thly

,ca

lls10

mo;

pedo

met

ers,

acco

mpa

nied

byco

unse

ling

and

prov

isio

nof

feed

back

;w

omen

prov

ided

larg

em

agne

tic,

eras

able

mon

thly

cale

ndar

toat

tach

tore

frige

rato

ran

dre

cord

num

ber

ofst

eps.

Hom

e-ba

sed

mai

lsup

port

(MS)

:M

onth

lyne

wsl

ette

rsw

ithpo

stag

epa

idm

ail-b

ack

card

tore

port

num

ber

ofst

eps

and

PAin

last

wee

k;fe

edba

cksh

eets

wer

ese

ntfro

mhe

alth

educ

ator

base

don

resp

onse

s;pr

izes

earn

edfo

rm

ailin

gba

ck(e

g,pe

ns,

wai

stpa

cks,

mug

s).

Both

grou

psin

corp

orat

edpe

ople

,pl

aces

,la

ngua

ge,

and

clot

hing

fam

iliar

tocu

lture

;ad

dres

sed

core

valu

es.

…PA

:At

10-w

kP�

MS�

263

kcal

/wk

vsM

S29

4kc

al/w

k,NS

Dbe

twee

nor

with

ingr

oups

.10

-wee

kto

12m

och

ange

,P�

MS:

adde

din

crea

seof

52kc

al/w

kvs

MS:

1014

kcal

/wk

less

,be

twee

ngr

oup

diffe

renc

e,P�

0.04

5,ES

�0.

24.

……

(Con

tinue

d)

Artinian et al Promoting Physical Activity and Dietary Changes 419

Tabl

e3.

Cont

inue

d

Refe

renc

e(s)

,Ye

ar,

Stud

yDe

sign

/Du

ratio

n(N

)Po

pula

tion/

Sam

ple

Inte

rven

tion

Outc

omes

Calo

ries/

Fat/F

ruits

and

Vege

tabl

es/F

iber

/Sod

ium

PAW

eigh

tBP

/Cho

lest

erol

/Glu

cose

/He

mog

lobi

nA1

c

Bulle

ret

al,74

1999

,2-

grou

pRC

T/6

and

18m

o(N

�76

6)

Empl

oyee

sfro

m93

wor

kgr

oups

.M

ean

age

43y,

43%

Hisp

anic

,6%

blac

k,75

%m

en,

�13

%�

11th

grad

eed

ucat

ion.

Allr

ecei

ved

gene

ral5

-a-d

ayin

foov

er18

mo.

Peer

Educ

atio

n(P

E):

last

9m

onth

sof

the

gene

ralp

rogr

am.

Subj

ects

had

indi

vidu

alse

ssio

nsw

ithpe

erle

ader

and

peer

-led

grou

pdi

scus

sion

sab

out

F/V;

activ

ities

for

child

ren;

prin

tm

ater

ials

abou

tF/

V.M

ater

ials

tosu

ppor

tbe

havi

oral

skill

s(ie

,F/

Vca

lend

ar,

reci

pes)

;ad

dres

sed

cultu

ralt

rend

sin

diet

,lo

w-li

tera

cygr

aphi

cs,

and

stor

ies.

Gene

ralE

duca

tion

only

:No

peer

educ

atio

ndu

ring

last

9m

o.

F/V:

inPE

grou

pat

18m

o,0.

77an

d0.

46in

crea

ses

inda

ilyF/

Vse

rvin

gspe

rFF

Q,an

dre

call

P�0.

001,

P�0.

002,

resp

ectiv

ely.

……

…

Cam

pbel

let

al,76

1999

,cl

uste

rra

ndom

ized

2-gr

oup

RCT/

2y

(N�

2519

)

Recr

uite

dfro

m50

blac

kch

urch

esin

10ru

ralN

orth

Caro

lina

coun

ties.

98%

blac

k,m

ean

age

53.8

y,73

%fe

mal

e,59

%in

com

e�

$20

000,

67%

�HS

educ

atio

n.

I:5-

a-da

ypr

ogra

m—

20-m

oin

divid

ual,

soci

alne

twor

kan

dco

mm

unity

-leve

lac

tiviti

esem

phas

izing

F/V

�2

educ

atio

nals

essio

nsre

gard

ing

mod

ifyin

gco

okin

gm

etho

ds,s

erve

dm

ore

F/V

atch

urch

func

tions

;com

mun

ityco

aliti

ons

incl

uded

chur

chm

embe

rs,l

ocal

agen

cies

,gro

cers

,and

farm

ers

topl

anco

mm

unity

even

ts;c

hurc

h-in

itiat

edac

tiviti

es.M

ater

ials

prom

oted

loca

llygr

own

prod

uce;

lay

heal

thad

visor

sat

tend

edbi

mon

thly

train

ing

sess

ions

topr

ovid

eso

cial

supp

orta

ndad

vanc

est

age

ofch

ange

;pas

tors

prom

oted

proj

ect.

C:De

laye

din

terv

entio

n—no

prog

ram

until

the

final

follo

w-u

p.

F/V

serv

ings

per

FFQ:

at2-

yfo

llow

-up,

the

5-a-

day

grou

pco

nsum

ed0.

85F/

Vse

rvin

gsm

ore

than

the

dela

yed

inte

rven

tion

grou

p,P�

0.00

1.

……

…

Coat

eset

al,47

1999

,2-

grou

pRC

T/6,

12,

18m

os(N

�22

08)

100%

fem

ale,

mea

nag

e60

y,28

%bl

ack,

16%

Hisp

anic

,re

crui

ted

from

clin

ics

loca

ted

in3

sout

hern

stat

es,

16%

�$1

500

0in

com

e,11

%�

HSed

ucat

ion.

I:Va

ngua

rdW

omen

’sHe

alth

Tria

lmod

ified

toin

clud

ead

ditio

nalg

oals

.A

nutri

tioni

stas

sign

edpe

rson

alfa

tg

goal

san

dde

liver

ed�

10gr

oup

sess

ions

with

decr

easi

ngfre

quen

cyov

er2-

ype

riod.

For

indi

vidu

als

havi

ngdi

fficu

lty,

nutri

tioni

sts

prov

ided

indi

vidu

aliz

edse

ssio

ns;

each

sess

ion

incl

uded

nutri

tion

and

beha

vior

chan

gest

rate

gies

,cu

ltura

l(re

gion

al/e

thni

cfo

ods)

,la

ngua

gean

dlo

w-li

tera

cyse

nsiti

vein

form

atio

nw

asus

ed;

sess

ions

incl

uded

regi

onal

and

ethn

icfo

ods.

Staf

ffro

mva

ried

raci

al/e

thni

cba

ckgr

ound

s.C:

Subj

ects

rece

ived

pack

age

ofst

anda

rdm

ater

ials

ongo

oddi

etar

ypr

actic

esin

clud

ing

the

Diet

ary

Guid

elin

esfo

rAm

eric

ans.

CalE

nerg

y(k

cal):

At18

mo,

betw

een-

grou

p(I

vsC)

diffe

renc

eof

�23

3(�

355,

�11

1);F

ruits

(ser

vings

):I-C

diffe

renc

eof

0.53

(0.3

3,0.

73);

Vege

tabl

es(s

ervin

gs):

I-Cdi

ffere

nce

of0.

27(0

.07,

0.47

);Fa

t(%

ofen

ergy

):I-C

diffe

renc

eof

�11

.62

(�13

.07,

�10

.17)

;Sat

Fat%

ofen

ergy

:I-C

diffe

renc

eof

�3.

54(�

4.09

,�2.

99);

chol

este

rol

(mg)

:�74

.1(�

100.

5,�

47.6

).

……

…

Frie

set

al,81

2005

,2-

grou

pRC

T/1,

6,an

d12

mo

(N�

622)

Indi

vidu

als

from

3ru

ralV

irgin

iaph

ysic

ian

prac

tices

.36

.7%

blac

k,m

ean

age

46y,

65%

fem

ale,

17%

�$2

000

0/y

inco

me.

I:Ta

ilore

dfe

edba

ckpl

usse

lf-he

lp.

Feed

back

mai

led

and

incl

uded

aPC

Ple

tter,

2fe

edba

ckfo

rms

(fat

and

fiber

),an

d2

reco

mm

enda

tion

form

s(fa

t/fib

er).

Stru

ctur

edte

leph

one

coun

selin

gw

ithin

2w

ksto

rein

forc

em

aile

dfe

edba

ck,

addr

ess

need

sof

low

liter

ate.

Low

-lite

racy

self-

help

book

lets

mai

led

wee

kly

�4.

Acu

ltura

l,co

mm

unity

advi

sory

boar

dm

ade

deci

sion

sab

out

cont

ent

and

pict

ures

inin

terv

entio

nm

ater

ial.

C:De

laye

din

terv

entio

n.

Fibe

r:pe

rfa

tan

dfib

erqu

estio

nnai

re,

high

ersc

ores

�m

ore

fiber

.Ig

roup

:2.

24(0

.35)

atba

selin

e,2.

07(3

7)at

6m

o2.

12(0

.39)

at12

mo

vsC

grou

p:2.

24(0

.36)

atba

selin

e,2.

16(0

.37)

at6

mo,

and

2.16

(0.3

8)at

12m

o.Fa

tper

ques

tionn

aire

,low

ersc

ores

�le

ssdi

etar

yfa

t:Ig

roup

:0.

2.03

(0.3

5)at

base

line,

1.85

(0.3

4)at

6m

o,1.

87(0

.35)

at12

mo,

vsC

grou

p:2.

05(0

.33)

atba

selin

e,1.

97(0

.34)

at6

mo,

1.95

(0.3

4)at

12m

o.Fo

rfa

tan

dfib

er,I

grou

psig

nific

ant

impr

ovem

ento

ver

time

P�0.

05);

inte

ract

ion

betw

een

cond

ition

and

time

signi

fican

tP�

0.05

.

……

…

(Con

tinue

d)

420 Circulation July 27, 2010

Tabl

e3.

Cont

inue

d

Refe

renc

e(s)

,Ye

ar,

Stud

yDe

sign

/Du

ratio

n(N

)Po

pula

tion/

Sam

ple

Inte

rven

tion

Outc

omes

Calo

ries/

Fat/F

ruits

and

Vege

tabl

es/F

iber

/Sod

ium

PAW

eigh

tBP

/Cho

lest

erol

/Glu

cose

/He

mog

lobi

nA1

c

Hava

set

al,48

1998

,2-

grou

pra

ndom

ized

cros

sove

rde

sign

/8m

oan

d1

y(N

�31

22)

Wom

ense

rved

by16

WIC

prog

ram

sin

Mar

ylan

d.52

%bl

ack,

�66

%ag

e�

30y,

19%

�HS

educ

atio

n,ap

prox

imat

ely

44%

usin

gfo

odst

amps

.

I:3

com

pone

nts—

(1)

Stag

eof

chan

ge–

base

dnu

tritio

nse

ssio

nsco

nduc

ted

bype

ered

ucat

ors;

(2)

prin

ted

mat

eria

lsan

dvi

sual

rem

inde

rs;

(3)

dire

ctm

ail.

Thre

epe

er-le

d45

-min

grou

pdi

scus

sion

sov

er6-

mo

perio

d,go

al-b

ased

.St

ory-

base

dpr

int

mat

eria

lsan

dvi

deot

apes

abou

tF/

Vw

ere

used

.C:

Inte

rven

tion

dela

yed.

F/V:

Chan

gebe

twee

nba

selin

ean

d8

mo,

Igro

up�

0.56

�0.

11se

rvin

gsvs

Cgr

oup

�0.

13�

0.17

,be

twee

ngr

oup

P�0.

002.

At1

y,Ig

roup

adde

din

crea

seof

�0.

27�

0.09

serv

ings

vsC

grou

p�

0.27

�0.

06se

rvin

gs;

betw

een-

grou

pdi

ffere

nce,

P�0.

004

ES�

0.05

.

……

…

Keys

erlin

get

al,49

2002

,3-

grou

pRC

T/12

mo

(N�

167)

100%

wom

enw

ithty

pe2

DM,

100%

blac

k,m

ean

age

59y,

�33

%in

com

e�

$10

000/

y

A.Cl

inic

and

com

mun

ity:

Incl

inic

—4

mon

thly

visi

tsw

itha

nutri

tioni

stw

hoco

unse

led

abou

tdi

etan

dPA

and

tailo

red

itto

base

line

prac

tices

and

attit

udes

.In

com

mun

ity—

3gr

oup

sess

ions

and

12m

onth

lyte

leph

one

calls

from

ape

erco

unse

lor

who

prov

ided

soci

alsu

ppor

tan

dre

info

rced

beha

vior

chan

gego

als.

B.Cl

inic

only

:Sa

me

ascl

inic

desc

ribed

abov

e.C.

Min

imal

inte

rven

tion:

Educ

atio

nalp

amph

lets

mai

led

tosu

bjec

ts.

…PA

per

acce

lero

met

er:

Avs

Cgr

oups

,th

edi

ffere

nce

inad

just

edm

ean

for

PAw

as44

.1kc

al/d

,P�

0.00

5.B

vsC,

the

diffe

renc

ew

as33

.1kc

al/d

,P�

0.02

9.

……

Kum

anyi

ka,75

1999

,2-

grou

pRC

T/1

y(N

�33

0)

Blac

kad

ults

recr

uite

dfro

msu

perm

arke

tBP

scre

enin

gsag

ed40

–70

y.�

72%

fem

ale,

47%

liter

acy

less

than

eigh

thgr

ade

52%

�$1

500

0/y.

Alls

ubje

cts

tore

duce

fat,

chol

este

rol,

and

Nain

diet

bya

nutri

tioni

stev

ery

4m

oat

offic

evi

sits

.Al

lsub

ject

sre

ceiv

edso

me

CARD

ESm

ater

ials

that

cons

iste

dof

(a)

food

card

sw

ithph

otos

ofco

mm

onfo

ods

and

code

dw

ithsy

mbo

lsto

indi

cate

low

,m

ediu

m,

orhi

ghfa

t,ch

oles

tero

l,or

Naco

nten

t;(b

)a

42-p

age

nutri

tion

guid

e;(c

)25

-min

vide

oto

mot

ivat

ean

dsu

ppor

tch

ange

;an

d(d

)12

,10

–15-

min

audi

otap

esan

dac

com

pany

ing

wor

kshe

ets

topr

ovid

ein

fo.

CARD

ESm

ater

ials

wer

eat

fifth

toei

ghth

grad

ere

adin

gle

vels

.Fu

llIn

stru

ctio

n(F

):Su

bjec

tspa

rtici

pate

din

mon

thly

nutri

tion

clas

ses

for

4m

oaf

ter

enro

llmen

tin

whi

cha

CARD

ESvi

deo

was

view

ed;

guid

ance

prov

ided

abou

tau

diot

apes

and

wor

kshe

ets,

and

disc

ussi

onof

them

esin

audi

opr

ogra

ms.

Vide

opo

rtray

edAf

rican

Amer

ican

fam

ily.

Self-

Help

(SH)

:In

addi

tion

toco

unse

ling

ever

y4

mo,

subj

ects

rece

ived

self-

help

mat

eria

lsin

clud

ing

food

card

san

dnu

tritio

ngu

ide.

……

…Al

lNSD

betw

een

grou

ps.

Chan

gefro

mba

selin

e:To

tal

chol

este

rol

(mm

ol/L

):F

�0.

41�

0.07

fem

ale,

�0.

50�

0.12

mal

e,P�

0.00

01,

vsSH

�0.

43�

0.07

F,�

0.36

�0.

13m

ol/L

,P�

0.00

6.HD

L-C

(mm

ol/L

):F

0.3

(0.0

3)fe

mal

e,0.

01(0

.04)

mal

evs

SH�

0.02

(0.0

3)fe

mal

e,�

0.03

(0.0

5)m

ale.

NSD

with

in-g

roup

diffe

renc

e.LD

L-C

(mm

ol/L

):F

�0.

34(0

.07)

fem

ale,

�0.

36(0

.11)

mal

e,w

ithin

grou

pP�

0.00

1,vs

SH�

0.35

(0.0

7)fe

mal

e,�

0.31

(0.1

2)m

ale;

with

ingr

oup

P�0.

009.

SBP

(mm

Hg):

F�

7.4

(1.9

)vs

SH�

10.6

(1.9

),w

ithin

-gro

updi

ffere

nce,

P�0.

0001

.DB

P(m

mHg

):F

�3.

7(1

.1),

P�0.

0007

vsSH

grou

p�

6.6

(1.1

),P�

0.00

01.

(Con

tinue

d)

Artinian et al Promoting Physical Activity and Dietary Changes 421

Tabl

e3.

Cont

inue

d

Refe

renc

e(s)

,Ye

ar,

Stud

yDe

sign

/Du

ratio

n(N

)Po

pula

tion/

Sam

ple

Inte

rven

tion

Outc

omes

Calo

ries/

Fat/F

ruits

and

Vege

tabl

es/F

iber

/Sod

ium

PAW

eigh

tBP

/Cho

lest

erol

/Glu

cose

/He

mog

lobi

nA1

c

Race

tteet

al,51

2001

,qua

si-ex

perim

enta

l/1y

(N�

69)

100%

blac

k,em

ploy

ees

ofth

eUn

iver

sity

ofW

ashi

ngto

nm

edic

alce

nter

atris

kfo

rty

pe2

DM,

86%

fem

ale,

educ

atio

nan

din

com

eno

tre

porte

d.

I:As

sign

eddi

etgo

als

(ie,

decr

ease

fat

�14

g/d)

.Su

bjec

tsre

ceiv

eda

1-w

ken

ergy

-an

dfa

t-re

stric

ted

diet

prep

ared

bya

met

abol

icki

tche

nfo

llow

edby

alif

esty

lepr

ogra

man

din

crea

sed

PAfo

r1

year

.Su

bjec

tsre

ceiv

edPA

pres

crip

tion

and

help

abou

tho

wto

mee

tgo

als,

7-d

food

diar

ies

ever

y4

mo

and

exer

cise

logb

ooks

.Th

ere

wer

e:in

divi

dual

mee

tings

onre

ques

tov

er1-

ype

riod;

optio

nalb

imon

thly

grou

pm

eetin

gs;

mon

thly

tele

phon

eca

llsto

mai

ntai

nco

ntac

t.C:

Subj

ects

mat

ched

for

age,

body

wei

ght,

body

com

posi

tion,

and

gluc

ose

tole

ranc

e.Su

bjec

tsw

ere

invi

ted

toen

roll

inth

ein

terv

entio

non

com

plet

ion

ofth

est

udy.

……

Wei

ght

loss

:�

4.6

kgin

Ivs

�

0.3

kgin

C,P�

0.00

1.To

talc

hole

ster

ol(m

mol

/L):

�0.

3in

Ivs

�0.

4in

C,P�

0.00

1.Gl

ucos

eto

lera

nce

(GT)

:At

base

line

13in

Ihad

impa

ired

GT,

and

6ha

ddi

abet

icGT

;at

1y,

10ha

dno

rmal

GT,

4ha

dim

paire

dGT

,an

d5

had

diab

etic

GT.

Cont

rol:

nodi

ffere

nce

from

base

line.

Resn

icow

etal

,102

2001

,cl

uste

rra

ndom

ized

trial

/12

mo

(N�

861)

100%

blac

kch

urch

mem

bers

,m

ean

age

43.9

y,73

.3%

fem

ale,

�45

%ha

din

com

e�

$40

000,

�50

%ha

dat

leas

tso

me

colle

ge.

A.Co

mpa

rison

:St

anda

rdnu

tritio

nan

dcu

ltura

llyse

nsiti

veF/

Ved

ucat

ion

mat

eria

ls.

B.Se

lf-he

lp�

1cu

eca

ll:Se

lf-he

lpm

ater

ials

incl

uded

avi

deo,

cook

book

,pr

inte

ded

ucat

ion

mat

eria

ls,

quar

terly

new

slet

ters

,an

dot

her

cues

(mag

net,

pot-

hold

er,

eras

able

writ

ing

tabl

et).

Calls

prov

ided

cues

tous

ein

terv

entio

nm

ater

ials

.C.

Mul

ticom

pone

nt:

Mul

ticom

pone

ntse

lf-he

lpm

ater

ials

with

1cu

eca

llan

d3

mot

ivat

iona

lint

ervi

ewin

gco

unse

ling

calls

.

F/V:

Chan

gein

F/V

was

sign

ifica

ntly

grea

ter

ingr

oup

Cvs

grou

pA

orB.

The

net

diffe

renc

ebe

twee

ngr

oup

Aan

dC

was

1.38

,1.

03,

and

1.21

serv

ings

ofF/

Vpe

rda

yfo

rth

e2-

,7-

,an

d36

-item

FFQs

,re

spec

tivel

y.Th

ene

tdi

ffere

nce

betw

een

grou

pA

and

Bw

as1.

14,

1.10

,an

d0.

97.

……

…

Rosa

let

al,52

2005

,2-

grou

pRC

T/3

and

6m

o(N

�25

)

Adul

tsw

ithty

pe2

DMre

crui

ted

from

aco

mm

unity

.10

0%Hi

span

ic,

80%

fem

ale,

mea

nag

e62

.6y,

84%

�$1

000

0/y,

74%

less

than

oreq

ualt

oei

ghth

grad

e.

Allp

artic

ipan

tsre

ceiv

eda

book

let

desc

ribin

gim

porta

nce

oflif

esty

lefa

ctor

sin

DMan

dpr

ovid

ing

reco

mm

enda

tions

for

diet

,PA

,an

dSM

BG.

I:In

itial

1-h

indi

vidu

alse

ssio

npl

ustw

o15

-min

indi

vidu

alse

ssio

ns,

follo

wed

by10

wee

kly

2.5–

3h

grou

pse

ssio

nsan

dtw

o15

-min

indi

vidu

alse

ssio

nson

diab

etes

;ta

ilore

dto

liter

acy

leve

land

cultu

re,

incl

uded

:se

lf-m

onito

ring

logs

,st

epco

unte

rs.

Abi

lingu

alnu

rse,

nutri

tioni

st,

and

anas

sist

ant.

Inte

rven

tioni

stbi

lingu

alan

dkn

own

inco

mm

unity

.C:

Subj

ects

only

rece

ived

the

book

let

rece

ived

byal

lpar

ticip

ants

.

…NS

Din

incr

ease

dPA

betw

een

orw

ithin

grou

ps.

BMI:

NSD.

HbA1

c:de

crea

seat

6m

onth

sin

Iw

as�

0.85

%vs

�0.

12%

,P�

0.01

.To

talc

hole

ster

ol(m

g/dL

):�

2.0

inI,

�11

.2in

Cat

6m

o,NS

D.LD

L(m

g/dL

):�

3.2

inIv

s�

12.5

inC

at6

mo,

NSD.

SBP

and

DBP:

NSD.

Stat

enet

al,53

Ariz

ona

WIS

EWOM

AN,

2004

,3-

grou

pRC

T/12

mo

(N�

217)

Wom

enre

crui

ted

from

2Tu

cson

clin

ics,

mea

nag

e57

.2y,

75%

Hisp

anic

,in

com

e$9

737/

y.

Activ

eco

ntro

l—pr

ovid

erco

unse

ling

(AC-

PC):

Atea

chcl

inic

visi

t,NP

spr

ovid

edhe

alth

educ

atio

nbr

ochu

res,

disc

usse

dbe

nefit

san

dba

rrie

rsto

incr

easi

ngPA

and

F/V,

gave

beha

vior

chan

gepr

escr

iptio

n;su

gges

ted

goal

s15

0�m

in/w

kof

PAan

d5�

serv

ings

F/V

per

day.

Prov

ider

coun

selin

g�he

alth

edcl

asse

s(P

C�HE

):Co

unse

ling

plus

subj

ects

refe

rred

to2

educ

atio

ncl

asse

son

diet

and

PA;

also

am

onth

lyhe

alth

new

slet

ter

for

12m

o.Pr

ovid

erco

unse

ling�

heal

thed

ucat

ion

clas

ses�

CHW

prov

ided

soci

alsu

ppor

t(P

C�HE

�CH

W):

Coun

selin

gan

dhe

alth

educ

atio

ncl

asse

spl

ussu

bjec

tsre

ceiv

edse

miw

eekl

yto

mon

thly

tele

phon

eca

llsfro

mCH

Ws

topr

ovid

ein

fore

gard

ing

bene

fits

ofPA

and

F/V,

how

tom

odify

beha

vior

,bi

mon

thly

wal

kspr

ovid

eden

cour

agem

ent

tofin

dw

alki

ngpa

rtner

san

dsu

ppor

t.

F/V:

Chan

geat

12m

o,PC

�HE

�CH

W:

�0.

26�

�0.

5,1.

0vs

PC�

HE�

0.23

��

1.0,

0.5

vsPC

�0.

59�

�1.

2,0.

1,NS

Dal

lcom

paris

ons.

�7.

4%m

ore

wom

enw

hore

ceiv

edPC

�HE

�CH

Wpr

ogre

ssed

toea

ting

�5

F/V/

dth

anin

PC�

HE(�

8.3%

)or

PC(�

5.2%

),P�

0.05

,ES

�0.

07.

PAm

in/w

k:Ch

ange

from

base

line,

PC�

HE�

CHW

:�

22.8

(6.0

,39

.6),

P��

0.01

,vs

PC�

HE:

�22

.6(2

.2,

43.0

),P�

0.05

,vs

PC:

�15

.1(0

.5,

29.8

),P�

0.01

,ES

�0.

03.

BMI:

Chan

gefro

mba

selin

e,PC

�HE

�CH

W:

0.1

(�0.

3,0.

6)vs

PC�

HE:

�0.

7(�

0.1,

1.4)

vsPC

:�

0.1

(�0.

6,0.

5),

NSD

allc

ompa

rison

s.

Tota

lcho

lest

erol

(mg/

dL):

Chan

gefro

mba

selin

e,PC

�HE

�CH

W:

�8.

3(�

16.0

,�

0.7)

vsPC

�HE

:�

10.9

(�19

.9,

�1.

8)P�

0.05

vsPC

:�

6.1

(�13

.7,

1.4)

.SB

P(m

mHg

):PC

�HE

�CH

W:

�5.

1(�

8.9,

�1.

2)P�

0.01

NSD

inot

her

2gr

oups

.DB

P(m

mHg

):PC

�HE

�CH

W:

�1.

3(�

0.8,

3.3)

vsPC

�HE

.43

(�1.

6,2.

5)vs

PC�

3.4

(1.5

,5.

2).

(Con

tinue

d)

422 Circulation July 27, 2010

Tabl

e3.

Cont

inue

d

Refe

renc

e(s)

,Ye

ar,

Stud

yDe

sign

/Du

ratio

n(N

)Po

pula

tion/

Sam

ple

Inte

rven

tion

Outc

omes

Calo

ries/

Fat/F

ruits

and

Vege

tabl

es/F

iber

/Sod

ium

PAW

eigh

tBP

/Cho

lest

erol

/Glu

cose

/He

mog

lobi

nA1

c

Stod

dard

etal

,112

2004

,M

AW

ISEW

OMAN

Proj

ect,

2-gr

oup

RCT/

12m

o(N

�14

43)

Wom

en,

mea

nag

e58

y,79

%bl

ack,

70%

with

BMI�

25,

all

unin

sure

dor

unde

rinsu

red,

rete

ntio

n:80

%fo

rEI

,73

%fo

rM

I.

Allp

artic

ipan

tsre

ceiv

edlo

w-li

tera

cyfa

ctsh

eets

onCV

Dris

ks,

nutri

tion,

and

PA;

also

afo

llow

-up

scre

enin

gat

12m

o.M

inim

umIn

terv

entio

n(M

I):Su

bjec

tsre

ceiv

edco

mpr

ehen

sive

CVD

risk

asse

ssm

ent,

on-s

iteco

unse

ling,

educ

atio

n,re

ferr

al,

and

follo

w-u

pas

need

ed.

Enha

nced

Inte

rven

tion

(EI):

Subj

ects

rece

ived

sam

eas

MIp

lus

grou

ped

ucat

ion,

one-

on-o

nedi

etar

yan

dPA

coun

selin

g,gr

oup

activ

ities

such

asw

alki

ng.

F/V:

80%

MIv

s82

%EI

�5

serv

ings

/d,

P�0.

12.

Prop

ortio

nw

ithin

crea

sed

PA:

6%M

Ivs

18%

EI,

P�0.

04.

…Pr

opor

tion

with

norm

alBP

:73

%M

Ivs

82%

EI,

P�0.

80;

norm

alto

talc

hole

ster

ol:

74.6

%in

MIv

s81

%in

EI,

P�0.

63.

Yanc

eyet

al,59

2006

,2-

grou

pRC

T/2-

,6-

,an

d12

-mo

(N�

366)

Obes

ebl

ack

wom

enat

tend

ing

abl

ack-

owne

dgy

m.

Mea

nag

e45

.5y,

inco

me

$40

000–

$59

000/

y.

A1-

ygy

mm

embe

rshi

pw

asof

fere

dto

allp

artic

ipan

tsas

anin

cent

ive

topa

rtici

pate

inst

udy.

I:Su

bjec

tspa

rtici

pate

din

8w

eekl

y2-

hin

tera

ctiv

egr

oup

sess

ions

incl

udin

gPA

and

diet

ary

educ

atio

npr

omot

ing

low

-fat

com

plex

CHO

rich

diet

;pe

dom

eter

san

dex

erci

seba

nds

prov

ided

;di

etar

yre

calls

done

bydi

etiti

an3

or4

times

,pr

ovid

edfe

edba

ck.

Topr

ovid

eso

cial

supp

ort,

subj

ects

invi

ted

toco

me

togy

mw

itha

frien

d.In

stru

ctor

sw

ere

cultu

rally

/et

hnic

ally

mat

ched

tosu

bjec

ts.

C:Su

bjec

tsre

ceiv

ed8

wee

kly,

2-h

inte

ract

ive

sess

ions

onbl

ack

wom

en’s

heal

thto

pics

with

out

the

soci

alsu

ppor

tco

mpo

nent

.

…Fi

tnes

s,w

ithin

grou

p:Ig

roup

and

Cgr

oup

fitne

ssle

vels

(per

1-m

ileru

n/w

alk)

impr

oved

by1.

9an

d2.

3m

in,

resp

ectiv

ely

at12

mo.

With

ingr

oup

diffe

renc

es,

P�0.

0001

for

both

Iand

C;NS

Dbe

twee

ngr

oups

.

Wei

ght

(kg)

:Bo

thgr

oups

sign

ifica

ntly

heav

ier

at12

mo,

P�0.

001.

…

Yane

ket

al,55

2001

,2-

grou

pcl

uste

rRC

T/1

y(N

�52

9)

Allb

lack

wom

en,

mea

nag

e53

y,In

com

e�

$36

000/

y.No

te:

Ultim

atel

yth

est

anda

rdan

dsp

iritu

alin

terv

entio

nsop

erat

edid

entic

ally

(SI)

sinc

ew

omen

did

not

belie

veth

ere

coul

dbe

ach

urch

-bas

edpr

ogra

mw

ithou

tsp

iritu

ality

.St

anda

rdbe

havi

oral

inte

rven

tion

(SBI

):Su

bjec

tsat

tend

edki

ck-o

ffre

treat

for

1.5

days

,re

ceiv

edfe

edba

ckon

base

line

data

;al

sore

ceiv

ed20

wee

kly

grou

pse

ssio

nson

diet

and

PAfo

cusi

ngon

build

ing

self-

effic

acy

and

skill

s;ea

chse

ssio

nin

clud

edw

eigh

-ins,

tast

ete

sts,

cook

ing

dem

os,

and

30m

inof

mod

erat

e-in

tens

ityPA

.Af

ter

20w

ks,

lay-

led

wee

kly

sess

ions

prov

ided

info

/sup

port

for

rest

ofye

ar.

Chur

chsp

onso

red

year

lyev

ents

.Sp

iritu

alIn

terv

entio

n:W

eekl

yse

ssio

nsin

clud

edpr

ayer

and

heal

thm

essa

ges

enric

hed

with

scrip

ture

,ae

robi

csto

gosp

elm

usic

,or

prai

sean

dw

orsh

ipda

nce.

Self-

help

cont

roli

nter

vent

ion

(SH)

:Su

bjec

tsre

ceiv

edAH

Am

ater

ials

onhe

alth

yea

ting

and

PAan

din

form

atio

nta

rget

edto

subj

ects

’pe

rson

alsc

reen

ing

resu

lts.

Ener

gyin

take

(kca

l/d):

Chan

geat

1y,

�11

7fo

rSI

vs�

7fo

rSH

.W

ithin

grou

pP�

0.00

01fo

rSI

vsP�

0.81

90fo

rSH

.Be

twee

ngr

oup

P�0.

004.

Na(m

g/d)

:�

145

inSI

vs�

8SH

,w

ithin

grou

pP�

0.00

01an

dbe

twee

ngr

oup

P�0.

02.

Tota

lfat

(g/d

):Ch

ange

at1

y,�

8.1

inSI

vs�

2.3

inSI

,w

ithin

grou

pP�

0.00

01fo

rSI

and

0.23

74fo

rSH

,Bt

wgr

oup

P�0.

03.

…W

eigh

tlo

ss(lb

):Ch

ange

at1

y,�

1.1

SIvs

�0.

83in

SH,

w/g

roup

P�0.

009

betw

een

grou

pP�

0.00

08.

BP(m

mHg

):Ch

ange

at1

y,SB

P�

1.6

and

DBP

�0.

36in

SIvs

SBP

�0.

95an

dDB

P�

0.22

inSH

;w

ithin

grou

pP�

0.00

4fo

rSB

Pan

d0.

21fo

rDB

Pin

SI;

NSfo

rSH

;NS

Dbe

twee

ngr

oups

.

WIC

indi

cate

sW

omen

,In

fant

s,an

dCh

ildre

n;NP

,nu

rse

prac

titio

ner;

and

CHO,

carb

ohyd

rate

s.

Artinian et al Promoting Physical Activity and Dietary Changes 423

group differences for the majority of studies was small, rangingfrom 0.00 to 0.33, except for the preliminary study of Carels etal,15 that used motivational interviewing to augment behavioralintervention and reported an ES of 0.84.

Cognitive-Behavioral Strategies for PromotingBehavior ChangeCognitive-behavioral strategies are an essential component ofbehavior change interventions. These strategies focus on chang-ing how an individual thinks about themselves, their behaviors,and surrounding circumstances and how to modify their life-style. As illustrated in Tables 2 and 3, at least 2 or morestrategies were incorporated in studies that yielded favorableoutcomes.

Goal SettingSeveral lines of evidence indicate that setting goals at the outsetof the program is important to achieve the desired behaviorchange. Under most circumstances, setting specific goals leadsto higher performance compared with no goals or vague goals.16

Compared with individuals who have vague or absent goals,individuals who target a specific behavior change are morelikely to be successful.17,18 Such goals may vary by degree ofdifficulty, specificity, and complexity; for example, makingsome dietary changes can be complex and requires severalintended outcomes.19 The use of goals is more successful whenthe goals are specific in outcome, proximal in terms of attain-ment, and realistic in terms of the individual’s capability.20 Goalsthat focus on behavior (eg, increasing whole grain intake) ratherthan a physiological target (eg, improving low-density lipopro-tein [LDL] cholesterol or glucose levels) are preferable becausebehaviors are under a person’s more direct control and alsoobservable by the individual, whereas several factors (eg, genet-ics) can influence physiological targets.16,19,21,22

Setting appropriately ambitious goals is also important. Goalsthat are too difficult may not be attempted, whereas those viewedas too easy may not be taken seriously or provide a sense ofsatisfaction once achieved. Providing regular feedback on goalattainment is important to instill a sense of learning and mas-tery.16 Of the 74 trials described in Tables 2 and 3, 31 trials(42%) included goal-based diet and/or PA strategies.23–53 Posi-tive dietary or PA behavior changes were observed in all but235,46 of the trials. Goals either set by participants43,44,46,48,54 orassigned by the healthcare provider can lead to desired outcomes(eg, weight loss).26,38,53,55

Self-MonitoringThe purpose of self-monitoring is to increase one’s awarenessof physical cues and/or behaviors and to identify the barriersto changing a behavior. Self-monitoring facilitates recogni-tion of progress made toward the identified goal (eg, minutesof PA or number of calories consumed per day), thusproviding direct feedback. Self-based monitoring allows theindividual to assess progress with the program on his/herterms, removing barriers such as travel or scheduling con-straints associated with structured group programs. Self-monitoring interventions can be simple, such as pencil-and-paper logs of PA or dietary intake or charting of weight lost, stepstaken, or distance walked.23,26,27,29,35,36,38,40,42,46,50–52,56–59 Self-monitoring strategies can be provided and then left to the

discretion of the individual or applied in conjunction withexternal prompts incorporated into the behavior-change strat-egy. For example, such prompts can include scripted tele-phone messages or Internet e-mail reminders, specializedpersonal digital assistant (PDA) programs for monitoringdietary intake and PA, as well as both commercial andfree-of-charge Internet-based programs.35,36,57 Studies to datesuggest that electronic self-monitoring systems can be effec-tive for monitoring behavior changes. An advantage ofelectronic monitoring systems is their mobility, decreasingcost, and increasing availability; a potential limitation is theabsence of human interaction.

Both observational data60–64 and evidence from clinical tri-als26 –28,30,36,38,50,52 demonstrate the importance of self-monitoring in achieving behavior change. A recent meta-analy-sis found that PA intervention studies using self-monitoringdemonstrated larger effect sizes than studies without self-monitoring.65 In a recent trial of weight loss, participants whoself-monitored their food intake lost twice as much weight asthose who did not self-monitor.62 Frequency of self-monitoring,as well as detail and proximity in time to the recorded behavior,can influence efficacy of self-monitoring.62 In a study testinginterventions to promote weight loss, individuals in a combinedtherapy group who frequently recorded their weight achievedmore than twice the weight loss than those who recorded theirweight infrequently.28 In the Women’s Health Initiative DietaryModification Trial, a randomized controlled trial in nearly50 000 postmenopausal women, independent predictors of di-etary change at 1 year included younger age, more education,having a more optimistic personality, attending more interven-tion sessions, and submitting more self-monitoring records.64

Notably, at 3 years, the only predictors of continued dietarymaintenance were attending more sessions and submitting moreself-monitoring records.63,64 Among the 25 trials with sizableminority representation in Table 3, only 6 included interventionsthat described self-monitoring.42,46,50–52,59 Five of these 6 trialsthat included self-monitoring42,46,50–52 led to positive lifestylebehavior changes, compared with 13 of the 19 trials that didnot include self-monitoring. Thus, both in whites and minor-ity populations, self-monitoring appears to be an effectivecomplement to behavioral intervention strategies.

Frequent and Prolonged ContactCompared with single-session interventions, the evidencesuggests that programs that incorporate scheduled follow-upsessions as a core component are generally more effec-tive.25,26,28,41,43,47,52,55,66–69 Frequent contact with individualshelps establish trust between the provider and individual, acomponent of care especially important among racial/ethnicminority groups.70 Ongoing contacts can be delivered by variousmodes, including face-to-face, telephone, email or through theInternet.27,36,68,69,71 When combined with the use of group-basedinterventions, scheduled follow-up sessions provide several ad-vantages, including social support from the peer group, anincreased desire to succeed due to a sense of commitment to thegroup, and an opportunity to modify the program based onfeedback from group members or the program leaders.

Across all behavioral domains, it is well-established thatadherence to any new behavior will often decline as the

424 Circulation July 27, 2010

intervention is reduced or withdrawn. Evidence suggests thatas the frequency of contact decreases, achievement of initialbehavior change also decreases.72 Further, any alreadyachieved behavior change often diminishes over time asfrequency of the follow-up decreases, and particularly sowhen the intervention ceases entirely.41,59,68 Greater numbersand more prolonged time courses of follow-up sessionsfacilitate success across sequential stages of behavior change,such as new learning of diet and/or PA behavior changeskills, practicing of these skills, problem solving and findingsolutions to overcome relapse, integrating new diet and PAbehavioral skills into one’s daily routine, and learning skillsto facilitate maintenance of new behaviors.73 Among the trialsreviewed (Tables 2 and 3), the majority of interventions thatled to dietary or PA changes that lasted �12 months includedfollow-up contacts over at least 4 months.26,38,46,48,51,53,55,74–76

There are few data on critical time points for follow-up.Expert opinion suggests that 6 months is a critical time to assessmaintenance, but no data are available that compare this periodwith others between 3 and 12 months. Initial intervention andfollow-up should be early and often, incorporating the expecta-tion of self-monitoring and deliberate follow-up. In the absenceof conclusive data, expert opinion suggests that follow-upbeyond the initial visit could include visits at 6 weeks; then at 3,6, 9, and 12 months; and then every 6 months thereafter ifbehavior change adherence is successful. Lack of adherenceshould prompt more frequent follow-up, whether in person, bytelephone, or electronically. Further research is needed to con-firm the feasibility and effectiveness of this suggested timeframe versus other alternatives.

Feedback and ReinforcementHealthcare provider feedback helps individuals learn newdietary or PA behavioral skills by providing an externalmeasuring stick against which to assess their progress.77

Feedback about behavior performance can illuminate conse-quences of diet and PA behavior for an individual, which maymotivate individuals to continue a certain behavior or providedirection for adjusting behavior to reach a targeted goal.78

When goal setting is combined with receipt of performancefeedback, individuals can use information about their currentlevel of performance to set realistic goals for improvement.78

Evidence in Table 2 suggests that feedback is frequentlyincluded in successful behavior change interven-tions.24,27,29,30,32,33,36,44,46,52,55,57,69,71,79–81 Six of the 25 trialslisted in Table 3 described provision of feedback as part of theintervention. Five of these studies resulted in positive lifestylechanges.44,46,52,55,81 Of the successful trials, all interventionsincluded provision of feedback about the initial baselinescreening results, and several included further feedbackduring follow-up assessments. Feedback based on initialscreening can help individuals become aware of the need forbehavior change, and feedback during follow-up providesupdated information about ongoing behavior change efforts.

Self-Efficacy EnhancementSelf-efficacy, a component of social cognitive theory, describesan individual’s perception regarding his/her abilities to carry outactions necessary to perform certain behaviors (eg, makingchanges in diet or lifestyle).20 Perceived self-efficacy is a major

determinant of performance independent of an individual’sactual underlying skill.20 The strength of perceived self-efficacyis particularly important, as individuals are more likely to bothinitiate a behavior and continue their efforts until success isachieved if their perceived self-efficacy is higher.20 Thus en-hancement of an individual’s perceived self-efficacy can beincorporated into interventions to improve the likelihood ofsuccessful behavior change. Bandura’s theory suggests 4 sourcesof self-efficacy that can be drawn on and incorporated intointervention strategies to enhance self-efficacy.82 The sourcewith the greatest potential for increasing self-efficacy, masteryexperiences, entails having a person successfully achieve a goalthat is reasonable and proximal; for example, substituting fruitfor a high-calorie dessert or being able to walk 1 mile. A secondsource, vicarious experience, consists of the individual witness-ing someone who is similar in capability successfully performthe desired task; for example, observing patients exercise andimprove their physical function in cardiac rehabilitation orwatching a nonprofessional prepare a healthy meal. A thirdsource, verbal persuasion, entails the provider persuading theperson that he/she believes in the person’s capability to performthe task. This is the weakest source for improving self-efficacy,but can be implemented via telephone or other electronic modes.The fourth source, physiological feedback, entails interpreting tothe individual the meaning of different symptoms associatedwith behavior change. Examples include explaining that expe-riencing fewer symptoms with exertion is related to regularparticipation in a physical activity program or that feeling lessfatigued or more comfortable is related to weight loss.20 Anextensive body of evidence indicates that self-efficacy influencesbehavior change across all the behavior domains related to CVDrisk reduction.83–92 Self-efficacy enhancements were incorpo-rated into the interventions of several of the studies that yieldedfavorable outcomes.30,39,40,46,54,55,68,79,93

IncentivesThe efficacy of incentive programs to induce or support behav-ioral change has been most extensively studied at the workplace.The most commonly used incentives have been financial, suchas health premium reductions or direct cash payments/bonusesfor specific changes.94 Few interventions described in thisreview included incentives,34,57,76 and the return on investmentfrom them has not been widely assessed. Novel but untestedincentive strategies include rewards for employees frequentlyparking in the spaces located furthest away from the work site inthe company parking lot or lowering the charge for use of on-sitefitness facilities when frequency of use is higher.

ModelingModeling is a behavior change strategy that consists ofhaving the person observe another individual perform behav-iors (eg, engaging in PA or preparing healthy food) that arerelated to his/her goal. Among interventions described inTables 2 and 3, several incorporated modeling, including useof in-person or video cooking demonstrations and personalPA training (having credible individuals demonstrate how toexercise and have the individual practice with them ifpossible).25,43,54,55,75,95,96 Another modeling approach is tohave a person speak with someone who has been successfulin making behavior changes (eg, maintained weight loss or a

Artinian et al Promoting Physical Activity and Dietary Changes 425

PA program). Exposure to models that are credible toparticipants can be an effective strategy to enhance skills forchanging behavior and enhancing self-efficacy.82

Problem SolvingProblem solving consists of 5 steps: identifying and definingthe problem, brainstorming solutions, evaluating the pros andcons of potential solutions, implementing the solution plan, andevaluating its success.97 Problem solving can be used to help anindividual navigate barriers to behavior change (eg, negotiatingsupport from the family when attempting dietary change). It isimportant to have the individual do the brainstorming whendeveloping solutions and, when possible, to have the personpractice the skill.97 Tables 2 and 3 describe several studies thatincluded problem solving as a part of interventions that led topositive behavior change.31,32,39,41,43–45

Relapse PreventionRelapse prevention is an approach that makes a person awarethat it is normal to deviate episodically from the goal behavior,such as missing some scheduled exercise sessions or giving upon the program due to lapses. Individuals are taught to recognizepast situations that have placed them at risk for lapses from theirdietary or PA behavior change program (eg, vacations orcalendar holidays) and how to use behavioral and cognitivestrategies for handling these situations.30 Although few inter-ventions reviewed specifically addressed relapse preventionas a strategy,23,30,45 others may have indirectly addressedrelapse prevention through the inclusion of social sup-port,29,35,41,47,53,55,76,80 through problem solving to reducebarriers,31,32,39,41,44 or through a reinforcement program.98

Motivational InterviewingMotivational interviewing is a directive, individual-centeredcounseling style for eliciting behavior change with a centralpurpose of helping individuals to explore and resolve theirambivalence (ie, lack of readiness toward changing their behav-ior).99 Briefly, the 7 key principles that characterize the nature ofmotivational interviewing include the following: (1) motivationto change is elicited from the individual, rather than imposedfrom without; (2) it is the person’s task, not the counselor’s, toarticulate and resolve his or her ambivalence; (3) direct persua-sion is not an effective method for resolving ambivalence100,101;(4) the counseling style is generally a quiet and eliciting one; (5)the counselor is directive in helping the person to examine andresolve ambivalence; (6) readiness to change is not a person trait,but a fluctuating product of interpersonal interaction; and (7) thetherapeutic relationship is more like a partnership than one inwhich there are expert/recipient roles.100

Interventionist behaviors that are characteristic of motiva-tional interviewing include seeking to understand the per-son’s frame of reference, particularly via reflective listening,and expressing acceptance and affirmation; eliciting andselectively reinforcing the person’s own self-motivationalstatements, expressions of problem recognition, concern,desire and intention to change, and ability to change; moni-toring the person’s degree of readiness to change; ensuringthat resistance is not generated by jumping ahead of theindividual; and affirming the person’s freedom of choice andself-direction. Training and certification of the interventionist

is necessary to achieve optimal results. There are several printand electronic resources to help clinicians wanting to learnmore about motivational interviewing,101 including the fol-lowing Web site: http://www.motivationalinterview.org/training/trainers.html. Referral to allied professionals trainedin motivational interviewing is also an excellent option forindividuals ambivalent about behavior change.

Evidence suggests that motivational interviewing can facili-tate behavior change. A 2003 meta-analysis19 was conducted oncontrolled clinical trials investigating interventions that primarilyimplemented motivational interviewing principles. Four studiesdemonstrated a combined ES of 0.53 (95% CI, 0.32 to 0.74) fordiet and exercise, thereby indicating moderate efficacy. Addi-tional motivational interviewing studies reported increased fruitand vegetable consumption as part of general lifestyle change inwhites and blacks,32,102,103 firefighters,71 smokers,93 and collegestudents.104 Other studies demonstrated that motivational inter-viewing increased PA among women and/or individuals withdiabetes or obesity15,40,105 and black individuals with hyperten-sion.106 An array of studies have reported improved bodymass index or weight loss using motivational interviewing inworkers in Oregon,107 other occupational settings,105 blackindividuals with hypertension,106 and white females.15 Over-all, there is general consensus that motivational interviewingoffers an evidence-based approach for enhancing adherenceto behavioral interventions, including dietary and PA change.

Intervention Processes or Delivery Strategies

Targeting Single Behaviors Versus Multiple BehaviorsEvidence described in Tables 2 and 3 shows that inter-ventions may focus on changing only PA,34,46,69,108,109

only dietary behaviors,17,24,30,32,33,39,47,48,54,68,74–76,80,81,96,110 orboth.26–29,35,36,38,43,44,50,51,53,55,57,66,67,111–113 Studies that focuson multiple behaviors have generally applied the same type ofintervention strategy (eg, provision of education materials,counseling sessions, follow-up monitoring) to change eachspecific behavior. Results of these studies have been variable.Most reported positive results (ie, the desired change in bothPA and dietary behaviors). However, studies have not con-sistently resulted in improvements in related metabolic/vascular biomarkers (eg, serum lipids, blood pressure). Theresults of a meta-analysis of studies testing interventions toincrease PA among older adults indicated that interventionstargeting only PA resulted in higher ES than studies designedto change multiple health behaviors.65

There is limited knowledge about the relative benefits ofsimultaneous versus sequential delivery of multiple PA anddietary behavior change interventions in adults. In a randomizedtrial of 289 blacks with hypertension, participants were random-ized to 1 of 3 groups: (1) an in-clinic counseling session every 6months on smoking, reduced dietary salt intake, and PA,supplemented by use of motivational interviewing strategies bytelephone for 18 months; (2) a similar protocol that introduced 1behavior every 6 months; or (3) a 1-time referral to existinggroup classes.106 When examining individual target behaviors at6 months, 29.6% in the simultaneous, 16.5% in the sequential,and 13.4% in the usual care arms had reached the urine sodiumgoal (P�0.01 for the simultaneous versus the usual care groupand P�0.05 for the simultaneous versus the sequential group).

426 Circulation July 27, 2010

At 18 months, 20.3% in the simultaneous, 16.9% in the sequen-tial, and 10.1% in the usual care arms were negative for urinarycotinine (P�0.06 for the simultaneous group versus the usualcare group and P�0.08 for the overall trend in smokingcessation), whereas 6.5% in the simultaneous arm, 5.2% in thesequential arm, and 6.5% in the usual care arm were adherent to�2 target behaviors (all statistical contrasts resulted in P�0.05).In contrast, findings from another trial among 315 femalesmokers supported a sequential over simultaneous approach tomultiple behavior changes, including diet, exercise, and smokingcessation.114

It is worth noting that additional studies published later thanour time window or performed outside the United States havealso shown mixed results for superiority of sequential versussimultaneous intervention strategies.115,116 In 1 trial, at 6 months,the simultaneous strategy was superior for a fat intake interven-tion and for a subgroup of participants who did not meet physicalactivity recommendations at baseline.115 However, the sequen-tial intervention resulted in better maintenance of interventioneffects at 2 years.117 Thus, the relative merits of simultaneousversus sequential intervention are unresolved, and more studiescomparing these intervention modes are needed.

Print- or Media-Only Delivery StrategiesMedia messages, printed materials, and other nonindividualizedstrategies may be used to provide information to individuals toencourage PA and dietary change. In a study involving individ-uals with mild hypertension, the use of nonindividualized edu-cational mailers did not significantly decrease BP.118 Overall,self-help approaches that provide nonindividualized brochuresand other behavioral learning tools without any additionalpersonal counseling appear to produce little benefit.55

In contrast, in a study comparing the efficacy of nonindividu-alized self-help manuals versus motivationally matched reportsand manuals to promote PA adoption, both groups showedsignificant improvement in PA at 6 months, but the increase was50% greater among participants receiving motivationallymatched materials.79 The mode of delivery may also influenceefficacy. In a study comparing the effects of motivationallymatched print materials versus motivationally matched tele-phone counseling, both groups had significantly increased PA at6 months, but participants receiving the print materials weremore likely to maintain PA change at 12 months.69 Thus,whereas further research on optimal modes of delivery isneeded, the evidence suggests that individualized print or mediamaterial are more effective than nonindividualized ones.

Group, Individual, Technology, andMulticomponent-Based Delivery StrategiesFour general approaches can characterize interventions to mod-ify dietary intake and increase PA, including (1) group-basedinterventions, (2) individual-based interventions, (3) computer/technology-based (interactive session, personal or automatedtelephone calls) interventions, and (4) multicomponentinterventions.

Group-Based InterventionsGroup-based interventions are characterized by opportunitiesfor social interaction, support from others who are experienc-ing similar challenges in modifying their lifestyle, role

modeling, and positive observational learning.29 Group-basedapproaches are commonly used in randomized clinical trialsemploying standard behavioral interventions for weightloss,24,25,28,29,66,72,109 as well as in other trials using diet andPA changes to target CVD risk factors such as BP or bloodcholesterol.23,26,27,56,66,67,113 In a meta-analysis of studies thattested interventions to increase PA among older adults,group-based intervention delivery resulted in larger ES thanindividual-based interventions.65

Group-based interventions have been successful in bothwhite28 and minority populations.76 The majority of studies withminority populations (18/25) included group-based interventionstrategies.42,43,46–48,51–55,59,74–76,96,110,112 Minority populationsranged from being 100% black,42,43,51,55,75,76,102,103,119 73% to100% Hispanic,44,46,52,53,110 to smaller subsamples of blacksand/or Hispanics.26,45,47,48,50,54,74,93,96,112,113

Typically, group interventions are administered in a small,closed group format (eg, 7 to 10 members). Groups initially meetas often as weekly, with meeting frequency often decreasingover time.28,43 Sessions may be led by a lay person or aprofessional.43,46,56,58,76,113 Successful group-based interventionsincorporate didactic education, counseling strategies, and multi-ple behavior change strategies such as goal setting and self-monitoring.26,38 Some group-based programs have includedskill-building sessions such as food label reading; groceryshopping; methods for healthy cooking; practice using pedom-eters, exercise bands, or other exercise equipment; and walkinggroups.24,68 Of the trials in Table 3 with a group-based interven-tion delivery, approximately one third (n�9) incorporated theuse of skill-building strategies.43,46,47,54,55,59,74,76,112 Among these,all but 1 study46 demonstrated at least within-group positive changesin dietary or PA behaviors or improved CVD risk factors.

In group-based weight loss interventions, the greatestweight loss usually occurs within the first 6 months of thestudy.15,30,120 Regardless of type of diet or activity, investi-gators typically report that many individuals find it challeng-ing to maintain the reduced caloric intake and/or PA plan, andweight is often regained by many individuals as early as 4 to6 months into the program. A major challenge in weightmanagement is identifying strategies to assist individuals inmaintaining long-term weight loss.24,121 To achieve this,investigators have tried supplementing the group-based ap-proach by recruiting participants with friends and enhancingsocial support,29 providing home exercise equipment,109 us-ing aerobic or strength-training exercises,72 providing im-proved access to counselors through the Internet,36,57,122 andusing a stepped-care approach and motivational interviewingfor those who did not meet their weight loss goals.15 Thestudies found improvements in all groups, with smallbetween-group differences in energy and fat consumption orPA changes, suggesting that supplementary strategies to mostbasic group-based approaches do not have a major effect onefficacy; however, most approaches that include the basicelements of standard behavioral treatment will have a positiveeffect on eating and PA habits and will result in weight loss,at least for the short term.

Commercial programs that use the group approach and aself-monitoring system to guide food restrictions (eg, WeightWatchers) appear to be more effective than self-help approaches.

Artinian et al Promoting Physical Activity and Dietary Changes 427

For example, in a trial among 212 adults,123,124 greater weightreductions were observed at both 1 and 2 years in the commer-cial group compared with the self-help group, with accompany-ing improvements in BP, blood lipids, insulin, and glucoselevels. Although such commercial programs have many similar-ities to the empirically tested noncommercial ones describedabove, having access to continued group support and ongoingcontact for 2 years may be the salient features of these programscompared with a self-help approach. However, due to their cost,commercial programs may be less available to socioeconomi-cally disadvantaged populations.

Individual-Focused InterventionsIndividual-focused interventions allow tailoring or personal-ization of healthcare recommendations to the learner’s par-ticular health concerns and life context. Individualized coun-seling has been effectively provided by health educatorsand/or counselors,31,32,125 physicians,95 and/or other health-care professionals.30 A meta-analysis of randomized clinicaltrials testing interventions to promote PA among older adultsfound that individualized interventions consisting of a healthrisk appraisal, activity counseling, and/or cognitive-behavioral strategies resulted in increased PA levels for atleast short term (�1 year), compared with a control group.126

A wide range of individual-based strategies have beentested, including in-person, telephone, electronic, and com-bined approaches. For example, among the studies reviewed,individual-only approaches included 6 biweekly telephonesessions,30 3 monthly telephone sessions,31 one 8-minutephysician-provided counseling session during a clinic visit,95

three 30- to 45-minute face-to-face counseling sessions fol-lowed by 12 counseling telephone calls,125 and 2 face-to-face45-minute counseling sessions followed by two 5- to 10-minute telephone calls 3 and 6 weeks after the sessions.32

Combined individual-based approaches appear to be suc-cessful in creating behavior change. For example, the use ofpersonal goal setting and self-monitoring via individualtelephone counseling improved adherence to a cholesterol-lowering diet and reduced serum cholesterol compared withusual care.30 In another trial, supplementing clinician advicewith telephone counseling by a health educator was moreeffective in improving levels of PA than clinician advicealone.125 In a study comparing physician-delivered nutritioncounseling alone versus physician counseling combined within-office prompts to usual care,95 only the combined programdecreased participants’ saturated fat intake, weight, and LDLcholesterol. The average counseling time was 8.2 minutes,5.5 minutes more than in the control group.95 No studies wereidentified that examined the effects of in-office prompts only,in-office reminders only, or in-office dietary and/or PAassessment tools only on diet and/or PA behavior change;more research is needed in these areas.

Three studies that addressed individual-based CVD riskreduction in the practice setting were published earlier thanour time window of published articles or were performedoutside the United States but warrant mentioning here.127–129

In 1 study, nurses initiated interventions for smoking cessa-tion, exercise, and diet and drug therapies for hyperlipidemiaamong hospitalized individuals who had suffered an acute

myocardial infarction.127 They followed the study partici-pants after hospital discharge by telephone and mail contact.Compared with usual care, the intervention group reportedhigher functional capacity at 6 months and higher smokingcessation rates and lower LDL cholesterol at 12 months.127 Asecond study delivered a 4-year intervention to assist indi-viduals with coronary artery disease in meeting several CVDrisk reduction goals through improving diet and PA, smokingcessation, and drug therapy.128 After an individualized ses-sion with a nurse at baseline, individuals were followed-up bymail and telephone contact and seen every 3 months in theclinic. Compared with usual care, the intervention group hadless progression of coronary atherosclerosis and decreasedhospitalizations for cardiac events.128 This is one of the fewtrials of sufficient size and follow-up duration to demonstratethat PA and dietary changes lead to reductions in clinical endpoints. A third trial, EUROACTION, investigated the effi-cacy of a nurse-coordinated multidisciplinary, family-based(rather than individual-based) preventive cardiology programconducted in 8 European countries for both primary andsecondary prevention.129 Compared with usual care, moreindividuals and their partners in the intervention groupachieved recommended targets for PA and for fruit, vegeta-ble, saturated fat, and oily fish consumption. Central obesitywas also reduced. These findings indicate that a nurse-ledmultidisciplinary team approach, coupled with support andinvolvement of an individual’s partner and family, can yieldsignificant lifestyle improvements and cardiovascular riskfactor reductions.

Because the studies described here utilized interventions thatwere delivered at the individual level, cognitive-behavioralintervention strategies may also have been incorporated andimproved efficacy. For example, some studies incorporatedmotivational interviewing strategies32,93,103,125; some used goalsetting, feedback, and/or self-efficacy enhancement30,79; andothers used readiness to change31,45,69,104,125,130 or problem-solving31,32,44 strategies. Overall, individual-based interventionshave been shown to be successful, at least for the short term (upto 1 year). In studies with minority samples (Table 3), individualintervention approaches to promoting change seem to result insmaller or fewer changes in total diet or PA compared withgroup-only55 or combined individual- and group-based ap-proaches.26,38,47,51 Research has yet to establish when and forwhom individual-only approaches are most appropriate.

Further investigation should better quantify the processes andcomparative effects of specific individual interventions. Keyquestions include whether the type of provider (eg, nurse,physician) influences efficacy; what specific combination ofcognitive, behavioral, and informational strategy is most effective;and what are optimal strategies for including family members.

Computer/Technology-Based InterventionsWith the growth of computer technology and the Internet,health interventions are increasingly delivered online or withthe use of technology. Several advantages of Internet-basedinterventions have been cited,131 including ability to reachmany people with a single posting; easy storage of largeamounts of information; ease of updating information; abilityto provide personalized feedback; cost effectiveness and

428 Circulation July 27, 2010

convenience for users; ability to reach people suffering fromisolation or conditions that cause them to feel embarrassed orstigmatized; timeliness of access; user control of the inter-vention; supplier control of the intervention; and ease ofadapting information for specific populations.36,57,108,122,132

Several studies have employed the use of the Internetor computer-based programs to deliver education andcounseling interventions for weight loss and dietarychange.17,33–36,57,108,122,132 (Table 2). Three studies demon-strated that the combination of an Internet program (eg,weekly reporting and graphs of weight, recipes, and weightloss tips) plus E-counseling (eg, automated praise or feed-back) resulted in greater weight loss than use of the Internetprogram alone.36,57,122 Another study found that Internet-onlycounseling was as effective for weight loss at 6 or 12 monthsas Internet-only counseling plus monthly in-person counsel-ing.35 A strategy of interactive, computer-controlled tele-phone systems for educating participants about a healthy dietresulted in some improvements in fruit, fiber, and saturatedfat intake.17 A supermarket kiosk program providing onsitenutrition information also resulted in improvements in fat,fiber, fruit, and vegetable purchases and intake.33

A few US trials have evaluated the efficacy of Internet orcomputer-delivered interventions to increase PA.34,108,132 In 1small trial (N�65), use of a PA Web site and 12 weeklyE-mail tip sheets resulted in increased total minutes ofwalking, but not time spent in moderate PA at 1 and 3months, compared with a control group.34 In a larger andlonger randomized clinical trial, investigators compared amotivationally tailored Internet intervention to motivationallytailored print material and to publicly available PA Internetsites; at 6 and 12 months, there were no significant differ-ences in minutes of PA among the 3 groups.108

Few Internet studies have been conducted among minorityand/or socioeconomically disadvantaged populations. Inves-tigators have reported that low-literacy individuals may havedifficulty accessing information through the Internet becauseof suboptimal searching strategies (eg, use of nonspecificsearch terms), unwillingness to click on links, accessing Websites written at or above the 10th grade reading level, andperceived higher quantity and complexity of the informa-tion.133,134 An understanding of the target population appearsessential to optimize delivery of Internet-based diet and PAbehavior change interventions.

Overall, the results of these trials are mixed, but at least insome scenarios, the use of Web-based and computerizedmaterials appears to improve weight loss and certain dietarybehaviors; fewer studies have evaluated PA. Combinationsof technology-based approaches may be more effectivethan single interventions; for example, the addition ofE-counseling appeared to improve efficacy of Internet-basedprograms for weight loss.35 The use of the Internet can allowhealthcare providers to reach a greater number of sedentaryadults in a cost-effective manner, but several importantquestions remain unanswered, including effectiveness inlow-income and minority samples, utility for increasing PA,long-term sustainability, optimal components of Internetinterventions (eg, number of log-ins, E-mails, online chats)and relative efficacy versus traditional printed material.

Multicomponent Intervention Delivery StrategiesIn contrast to single strategies, most trials have evaluatedmulticomponent interventions (Tables 2 and 3). Multicompo-nent programs include combinations of technology/media; groupor individual-based delivery strategies such as interactivecomputer-based programs plus telephone follow-up and com-munity resource enhancement80; computerized assessment andfeedback plus videotapes, telephone follow-up, or individualcounseling32,39; physician advice plus motivational videotapes,telephone calls, and interactive mail135; group sessions plus individ-ual motivational interviewing15,40; or individual plus group ses-sions.38,41,58,111 In most multicomponent studies, various behav-ioral strategies were also included, including goal setting,self-monitoring, feedback,38–41,46,49–53,55,58,59,80,81,111 socialsupport,49,76 problem solving,39,41 or motivationalinterviewing.15,40,102

Among nonminority populations (Table 2), all 10 multicom-ponent intervention trials reviewed demonstrated positive di-etary and/or PA outcomes. Among the 16 multicomponentintervention trials involving minority populations (Table 3),most 47–53,55,74–76,81,102,112 demonstrated some positive changes ineither dietary and/or PA behavior. The 2 trials of multicompo-nent interventions that did not lead to dietary or PA changes46,59

may have been limited by insufficient duration or lack ofeffective combination of behavior change strategies. The opti-mal combination of behavior change strategies in multicompo-nent interventions has yet to be determined.

As part of a personalized, medical office-based interven-tion focused on dietary self-management for individuals withtype 1 or 2 diabetes, a computerized assessment of potentialdietary barriers was used to immediately generate 2 printedfeedback forms that were provided in combination withpersonalized counseling and other self-help materials.39 Oneyear later, significant decreases were observed in total fatintake and serum cholesterol levels, but not hemoglobin A1clevels. One of the most successful multicomponent studieshas been the Diabetes Prevention Program (DPP).38 The DPPused individual counseling in the intensive lifestyle interven-tion arm of the trial, with goals of 7% weight loss and 150minutes per week of PA.38 Compared with a control groupthat received some group education, participants assigned tothe lifestyle intervention had greater dietary changes, in-creased levels of leisure-time PA, and greater weight loss.Incidence of diabetes and metabolic syndrome were reducedby 58% and 41% in the lifestyle and control groups, respec-tively. Notably, the effects of the intensive lifestyle treatmentdid not differ significantly by sex, race, or ethnicity. TheLook Ahead Trial,111 an ongoing, multicenter randomizedclinical trial of participants with type 2 diabetes mellitus,combined individual and group sessions. At 1 year, the trialreported significantly greater weight loss, improved fitness,and lower mean hemoglobin A1c in the combined groupcompared with those who received diabetes support andeducation through a limited number of group-only meetings.

Special Considerations for Interventions WithMinority and SocioeconomicallyDisadvantaged PopulationsIn the United States, numerous racial and ethnic groups existwith diverse cultural norms, values, attitudes, beliefs, and

Artinian et al Promoting Physical Activity and Dietary Changes 429

lifestyle patterns. Interventions designed to change dietaryand/or PA behavior in 1 population group may be lesseffective in another group, especially when the population iseducationally or economically disadvantaged or differs incultural health beliefs or practices from the population inwhich the intervention was initially tested. Optimally, meth-ods to design or adapt interventions should be directlyassessed in diverse populations and settings. Relatively fewerstudies (n�25) within the specified time period for thisreview (1997 to 2007) evaluated samples other than whitemiddle- or upper middle-class Americans. The most com-monly studied minorities were blacks and Hispanics. Studiesin Hispanic populations often did not adequately addresslinguistic competency. Although intervention studies havebeen conducted that included Asian American and NativeAmerican populations, in most, numbers were insufficient toconduct ethnic-specific subgroup analyses. Table 3 displaysthe 25 studies that included ethnic minorities or low-incomeparticipants that were reviewed and that provide the basis foradditional discussion about implementing dietary and PAchange interventions in these population subgroups. It isimportant to recognize that additional diversity occurs withinracial/ethnic groups, so that intervention designs shouldconsider the potentially diverse values, beliefs, and socioeco-nomic characteristics within each group.

Setting in Which Healthcare Is DeliveredFor interventions in minority or socially and/or economicallydisadvantaged populations, an important consideration isidentifying a setting to minimize the barriers to access theintervention. Once access is established, Table 3 indicatesthat interventions conducted in work sites, clinics, communi-ties, and churches can lead to improved dietary intake and PAlevels among blacks and/or Hispanics.

Peer/Lay Led Versus Professionally LedResearch suggests that people are more likely to hear andpersonalize messages, and thus to change their attitudes andbehaviors, if they believe the messenger is similar to themand faces the same concerns and pressures.136 It is thereforeimportant to consider when a person may be more likely tobelieve a lay health advisor versus health professionalthought to be an authority figure. Lay health advisors, peereducators, or community health workers are trusted commu-nity members and usually live in the same communities,speak the same language, have similar values and beliefs, andunderstand the cultural context of the minority target popu-lation.137,138 Lay leaders can improve the quantity of messagesabout healthy behavior and tailor messages to the unique needsand culture of the target population.74 The homophily forethnicity (ie, the tendency of individuals to associate and bondwith similar others) is important and may affect whether layadvisors or healthcare professionals are more effective.

Of the 25 trials reviewed (Table 3), 3 tested lay-led group orindividual-level interventions,43,48,74 and 4 tested interventionsthat combined professional and lay educators.52,53,55,76 All thesetrials generally showed some positive changes related to diet andor weight. The trials using both professionals and lay leadersalso further led to positive outcomes in diet,55,76 blood choles-

terol and BP,53,55 PA,53 and hemoglobin A1c at follow-up.52 It isalso important to note that several studies demonstrated thatprofessional-only led interventions can also lead to improveddiet and PA changes in minorities.42,45–47,93,103 Given the well-documented history of discrimination toward minorities inhealthcare settings, and a greater awareness of historical discrim-ination against blacks,70,139–141 expert opinion agrees that pro-vider capacity for trust building, communication skills, andcultural sensitivity are important ingredients of professional-ledinterventions.

Cultural SensitivityCultural sensitivity in health promotion interventions refers todesigning and delivering interventions that are relevant andacceptable within the cultural framework of the target popula-tion.142 Development of culturally sensitive interventions de-pends on knowledge of the history, values, belief systems, andbehaviors of the members of the target minority group. Theability to overcome language barriers faced by non–English-speaking immigrants is also necessary.143 Of the 25 trialsreviewed (Table 3), 18 designed culturally sensitive interven-tions and had mixed results.43–47,52,55,59,74–76,81,93,96,102,103,110,144

In comparison, the results of the trials not including culturallysensitive interventions42,48,49,51,53,54,112 demonstrated within-and/or between-group differences in diet, PA, or related meta-bolic/vascular biomarkers. Thus cultural sensitivity alone is notsufficient and needs to be combined with essential behaviorchange strategies to produce positive outcomes.

Literacy Level SensitivityWithout adequate literacy skills, individuals cannot read health-related materials. When working with persons of lower educa-tional levels, literacy assessment and modification of methodsfor providing health information are useful. Effective strategiesinclude use of audiovisual and interactive multimedia rather thanprint media; use of simple messages with short sentences, 1- or2-syllable words, and large print with lots of space; and nonre-liance on the Internet for provision of information.54,110,145,146

Seven of the 25 studies described in Table 3 used interventionssensitive to literacy levels44,45,47,52,54,74,81; 6 of these44,45,47,52,74,81

resulted in some positive outcomes. The trial with null out-comes54 lacked other intervention components such as specificbehavioral goals, self-monitoring, or feedback that may havelessened the efficacy of the intervention.

Barriers to Behavior ChangeReported barriers to healthy eating among the disadvantagedand/or minority groups include poor dental health, lack ofaccess to quality produce at affordable prices, inability to findethnically preferred fruits and vegetables in local markets,transportation problems, family customs/habits, social andcultural symbolism of certain foods, and low price and easyaccess to snack foods.147–152 Neighborhoods in which lowersocioeconomic status individuals often live may not be condu-cive to exercise due to high traffic, poor lighting, waste sites,infrastructure deterioration, high crime rates,151,153 and lack ofavailability of facilities that enable and promote PA.154,155 Thusassessment of barriers to behavior change should be part ofinterventions targeting these population groups.

430 Circulation July 27, 2010

AcculturationEvidence supports that acculturation of immigrants to theUnited States negatively influences healthy dietary pat-terns.156,157 For example, highly acculturated Hispanics atefewer servings of fruits and vegetables per day comparedwith those not highly acculturated, suggesting that healthcareproviders need to encourage immigrants to retain traditionalhealthful eating patterns. Thus assessment of acculturationmay be helpful in designing and implementing interventionsto improve dietary habits in immigrant groups.

Fostering Initiation and Maintenance ofBehavior ChangeSeveral factors influence the design of optimal interventionsand may influence a person’s ability to adopt and maintainnew lifestyle behaviors. First, various psychological factorsenable individuals to adopt as well as sustain new behaviorslong term. For initiating a behavior, persons’ consideration ofthe anticipated benefits must compare favorably to theircurrent situation, and they need to hold favorable expectan-cies regarding future outcomes.4,158 The decision to maintaina behavior is dependent, at least in part, on whether theachieved outcomes associated with the new behavior patternare sufficiently desirable to sustain the behavior (ie, on theindividual’s perceived satisfaction with the outcomes of thatbehavior change). Most individuals have clear expectationsabout what a new lifestyle will provide; if their experiencesdo not meet those expectations, they will be dissatisfied andless motivated to maintain it, particularly in environmentsthat are frequently not supportive of healthy choices.

Other factors that may influence adoption and maintenanceof new PA or dietary behavior include:

● Age—Evidence suggests that older age per se does notsignificantly reduce the response to PA or dietary interven-tions. Older age may be associated with more healthfuldietary patterns and better adherence, such as higherconsumption of fruits.159–163 In the DPP trial, the greatestrisk reduction in response to the lifestyle intervention wasseen in the oldest age group, suggesting better adherenceand/or efficacy in this group. However, although olderadults on average may have better adherence, some mayhave barriers to overcome to achieve this adherence. Forexample, some older adults may be at particular risk forpoor dietary habits, especially if they live alone and/or havelow incomes. Although younger adults are more likely tocite time as the main constraint to exercise,164 older adultsmost frequently cite poor health, including pain, reducedmobility, and low endurance.165

● Sex—Lower PA levels in women than men are generallyreported.166–168 Women, however, are reported to havebetter eating habits than men.169–174

● Better health status has been associated with greater levelsof PA.175–177

● Obesity, higher body mass index, and smoking are associ-ated with lower PA levels.175,177–179

● Presence of comorbid conditions and depression negativelyimpact adherence to most lifestyle change regimens.180–183

● Deficits in cognitive processing and memory can reduceadherence, particularly for complex regimens.184,185

● Individual differences in perception and assessment of costsand benefits of behavior change, when different from providerexpectations, may alter responsiveness to interventions.186

● Conscientiousness and self-efficacy each have been re-ported to favorably impact adherence.187

● Somatic factors related to side effects negatively impactadherence to most regimens.180,181,188

● Availability of social support positively influences PA andhealthy food choices.29,189–192

● It is important to consider the above-listed factors as wellas the knowledge levels and skills of the individual beforeimplementing therapeutic lifestyle changes.

RecommendationsTable 4 provides evidence-based and expert opinion recom-mendations on designing and implementing PA and dietaryinterventions in adults. Recommendations are organized toaid clinicians: to use cognitive-behavioral strategies to assistadults to adopt and maintain healthy dietary and PA targets;to make decisions about behavior change intervention pro-cesses and delivery strategies; and to modify interventions foraddressing cultural and social context variables that influencebehavioral change. The level of evidence base for thesedifferent recommendations varies; a few are supported morestrongly by expert opinion or case study rather than directresearch findings. The strength and types of evidence used toderive each recommendation are indicated in Table 4.

Subsequent to May 2007, when the literature review wascompleted for this publication, results from a few landmarkstudies conducted in large study populations were published.These include the POUNDS Lost Study (N�811), which com-pared 4 diets for weight loss, and the 1-year weight loss datafrom the Look AHEAD Study (N�5145).193–195 In each case,weight loss itself, however it was achieved, was associated withreduced CVD risk. In addition to a specified dietary intervention,these studies included behavioral counseling strategies that aredescribed in detail in this article, which were implemented topromote behavior modification for weight loss and to comple-ment the dietary and/or physical activity components of theintervention. Consistent with the recommendations made inTable 4 in the present article, weight loss success was attributedto the best adherence to behavior and dietary recommenda-tions.193–195 The results of these studies add further and consis-tent support for the recommendations made herein that includestate of the art behavior change strategies to counsel individualsin order to promote weight loss as needed along with the dietaryand physical activity changes to maximize reduction in CVD risk.

Implications for Healthcare Policy and forOther Policy

Changes in healthcare policies are needed to make it morefeasible to follow the recommendations made in this state-ment. Providers face numerous barriers to assessment andcounseling for therapeutic lifestyle change. Although a majorprovider barrier to adherence in the acute inpatient setting isa focus on the acuity of the presenting problem, the major

Artinian et al Promoting Physical Activity and Dietary Changes 431

provider barrier in the outpatient ambulatory setting is limitedresources for counseling and sustained follow-up support.196

Across all settings are the persistent and ever-growing issuesof provider time restraints, lack of financial incentives orreimbursement for health promotion, skepticism regardingwhether health promotion counseling will result in behaviorchange, insufficient information about the most effectivecounseling strategies, lack of skills necessary to providepositive individualized counseling using both verbal and non-verbal communication skills, and doubts about the likelihood oflifestyle changes resulting in the desired outcome.197–199 Physi-cians and nurses often cite their own lack of confidence in aperson’s ability to use preventive strategies for long-termbehavior change.200–205

Healthcare delivery systems need to address policy toensure an environment that supports preventive interven-tions.206 Examples of healthcare system policies needed tostrengthen the provider’s ability to promote PA and dietarylifestyle changes include: use of tracking, reporting, andfeedback systems; assessment of practice goals and bench-marks; availability of toolkits containing assessment toolsand diet and PA behavior change guidelines; education andtraining for providers, including cultural sensitivity training;provision of incentives that are tied to desired individual andprovider outcomes; and development of mechanisms forobtaining data on diet and PA behavior before a providervisit. It is encouraging that the American College of Cardi-ology Foundation/AHA’s 2009 performance measures forprimary prevention of CVD in adults include lifestyle coun-seling.207 Performance measures for diet and PA interventionare critical to improve the value placed on these interventionsby the reimbursement system.207

It is important to note that other factors not included in thisreview will affect whether our evidence-informed recommenda-tions are feasible for implementation, will result in improvedlevels of cardiovascular risk factors, and will prevent clinicalevents. Policies that foster individual healthy lifestyle choicesare needed. For example, insurance premiums could be loweredfor those who participate in programs around healthy diet andPA behaviors. Legislative initiatives geared toward providingmore complete and accessible information to the general publicor limiting the use of certain food components in the foodsupply, coupled with guidance on how to use that information orimplement the policy, has been shown to positively influencefood choices and foods available. For example, mandatorycalorie labeling at point of purchase enacted by the New YorkCity Health Department has provided expanded information forindividuals about their food choices.208 This legislatively man-dated regulation has been coupled with large-scale educationinitiatives on how to use the information. An environmentallegislative initiative also championed by New York City is thestaged phase-out of partially hydrogenated fat by food purvey-ors.209,210 Extensive support systems to the food producers toprovide advice and assistance in how to make the change andwhere to obtain the alternate fats were key ingredients in thesuccess of the program. Many other cities have adopted or havelegislative efforts underway to mandate law that food purveyorsphase out industrially produced trans fats. As of October 2009,California passed legislation to limit trans fats, and numerous

Table 4. Recommendations for Counseling Individuals toPromote Dietary and PA Changes to Reduce CardiovascularDisease Risk

Cognitive-behavioral strategies for promoting behavior changeClass I

● Design interventions to target dietary and PA behaviors withspecific, proximal goals goal setting. (Level of evidence: A)

● Provide feedback on progress toward goals. (Level of evidence: A)● Provide strategies for self-monitoring. (Level of evidence: A)● Establish a plan for frequency and duration of follow-up contacts (eg,

in-person, oral, written, electronic) in accordance with individual needsto assess and reinforce progress toward goal achievement. (Level ofevidence: A)

● Utilize motivational interviewing strategies, particularly when anindividual is resistant or ambivalent about dietary and PA behaviorchange. (Level of evidence: A)

● Provide for direct or peer-based long-term support and follow-up, suchas referral to ongoing community-based programs, to offset thecommon occurrence of declining adherence that typically begins at4–6 months in most behavior change programs. (Level of evidence: B)

● Incorporate strategies to build self-efficacy into the intervention.(Level of evidence: A)

● Use a combination of �2 of the above strategies (eg, goal setting,feedback, self-monitoring, follow-up, motivational interviewing,self-efficacy) in an intervention. (Level of evidence: A)

Class II● Use incentives, modeling, and problem solving strategies. (Level of

evidence: B)Intervention processes and/or delivery strategies

Class I● Use individual- or group-based strategies. (Level of evidence: A)● Use individual-oriented sessions to assess where the individual is in

relation to behavior change, to jointly identify the goals for riskreduction or improved cardiovascular health, and to develop apersonalized plan to achieve it. (Level of evidence: A)

● Use group sessions with cognitive-behavioral strategies to teachskills to modify the diet and develop a PA program, to provide rolemodeling and positive observational learning, and to maximize thebenefits of peer support and group problem solving. (Level ofevidence: A)

● For appropriate target populations, use Internet- andcomputer-based programs to target dietary and PA change;evidence is less for targeting PA alone; adding a form ofE-counseling improves outcomes. (Level of evidence: B)

Class IIa● Use individualized rather than nonindividualized print- or media-only

delivery strategies. (Level of evidence: A)Addressing cultural and social context variables that influence behavioralchange

Class IIa● Utilize church, community, work, or clinic settings for delivery of

interventions. (Level of evidence: B)● Use a multiple-component delivery strategy that includes a group

component rather than individual-only or group-only approaches.(Level of evidence: A)

● Use culturally adapted strategies, including use of peer or lay healthadvisors to increase trust; tailor health messages and counselingstrategies to be sensitive to the cultural beliefs, values, language,literacy, and customs of the target population. (Level of evidence: A)

● Use problem solving to address barriers to PA and dietary change,such as lack of access to affordable healthier foods, lack ofresources for PA, transportation barriers, and poor local safety. (Levelof evidence: B)

PA indicates physical activity.

432 Circulation July 27, 2010

other states have similar legislation under review (http://www.ncsl.org/default.aspx?tabid�14362).These types of ap-proaches, if enacted in a collaborative fashion, can serve to shapean environment where optimal lifestyle choices are available andin some cases are the “default” options.

Community environments have been extensively investi-gated in relation to PA and diet.9,211–216 Special efforts bycommunity groups, businesses, and government to increasethe availability of healthier food and PA choices will com-plement provider interventions to implement lifestylechanges. Policies for providing wide and safe routes forwalking and biking in communities and along state andfederal roads, maintaining public parks, reducing exposure tounhealthy fast food or to high-calorie/low-nutrient foods,menu labeling, and increasing access and availability tohealthy foods appear crucial.

Workplace policies designed to engage employees toachieve optimal health, as well as provide opportunities fororganized PA (eg, lunch hour walking programs, instructor-led group exercise) and more healthy eating options (eg,cafeterias, vending machines, healthy taste clubs) will com-plement provider efforts to implement lifestyle change. Asynthesis of older studies indicated that a point-of-decisionprompt to use the stairs instead of an elevator or escalatorresulted in a median increase in stair climbing of 53.9%.189

More recent studies have confirmed the positive effects ofsignage on stair usage in public buildings190 and have shownthat experimentally reducing the availability of escalators andmodeling more active behaviors increase stair use.217,218 Insummary, healthcare system policy and other policy changesare needed to increase the effectiveness of our evidence-based recommendations to improve diet and PA behaviors.

Where Do We Go From Here? Implicationsfor Future Research

Evidence suggests that cognitive-behavioral strategies are anessential component of interventions targeting dietary and PAbehavior change. We know that individual, group, andmulticomponent intervention delivery strategies are effective;however, we need comparative studies to demonstrate therelative strengths and weaknesses of implementing multicom-ponent strategies versus any single strategy. We also knowthat computer/Internet-based delivery strategies are effectivefor selected populations. However, the ability for newertechnologies such as text messaging and social networkingtools such as Health Vault, Twitter, and Facebook to facilitatedietary and PA change needs to be determined.

There are many other gaps in our current knowledge aboutpromoting lifestyle change. Comparative studies evaluating theeffectiveness and intensity of diverse interventions are needed toidentify the interventions most likely to succeed in both initiationand maintenance of diet and PA lifestyle changes. Optimalfollow-up strategies to maximize the duration of change needs tobe addressed in future studies. We do not know the specificdesign features that determine which interventions are mosteffective for whom (eg, young-old, male-female, high-lowsocioeconomic status) and at what cost. More knowledge abouttreatment receptivity or efficacy across different sex, racial,ethnic, or socioeconomic groups is needed. Many of the studies

reviewed included samples of predominantly well-educatedwhites, and several studies targeted blacks and Hispanics; morestudies that target other racial and ethnic minorities such asAsians, Native Americans, or Arab Americans are neededbecause these groups are also at risk for CVD.219 The majorityof studies reviewed (�57%) contained samples that were pre-dominantly (�70%) female. Although this representation ofwomen is an improvement from that reported in an earlierreview of 49 studies of compliance to pharmacological, exercise,nutritional, and smoking cessation therapies (85% male),187 westill do not know the extent to which lifestyle change interven-tions should be tailored to sex. The absence of males in most ofthe weight loss trials may reflect reluctance of some investiga-tors to mix sexes,29,36,57,109 as well as lower numbers of maleswho seek weight loss treatment or respond to recruitment effortsfor studies that include men.24,62 More research is needed onweight loss interventions in men, among whom the obesityepidemic is similarly rampant.220

Although the studies reviewed examined the influence ofbehavior change on surrogate end points such as lipid or BPchanges, few examined the influence of behavior change onCVD events, mortality, hospitalizations, or quality of life.221,222

More studies with longer-term follow-up of individuals who areable to maintain behavior change are needed to allow evaluationof these clinical end points.

The next generation of studies should also investigate howindividual interventions interact with the multiple levels ofenvironmental influences on PA and dietary behavior change.Both increased scope and detail of investigation are needed tounderstand the combined effects of individual behavior, health-care system, and sociocultural and environmental factors.Health-promoting community design,223 active-living communi-ties,224 and providing a healthier food environment should beincorporated into future studies to investigate multiple levels ofenvironmental influences on health behavior.

Lifestyle interventions often target constructs based onsocial cognitive theory (eg, self-efficacy, self-regulation[self-monitoring, goal-setting, feedback], social support, ob-servational learning) or the trans-theoretical model of change(eg, stages of motivational readiness). More evidence isneeded to determine whether one or the other theoreticalapproach may be better in specific circumstances.

Lack of reimbursement for therapies targeting dietary andPA lifestyle change is a barrier for healthcare providers. Inorder to establish a case for reimbursement, we need to betterunderstand the expected costs and cost-effectiveness of suchinterventions in the community. Future research must morecarefully examine effectiveness of behavior change strategiesin routine clinical practice, as opposed to efficacy trials thatexamine interventions under more structured ideal conditions.The efficacy of different behavior change strategies shouldalso be assessed in diverse practice settings with diversepopulations to understand generalizability and factors thatinfluence it. Finally, we need to understand how to translateand feasibly deliver these evidenced-based strategies intohealth practice, through delivery, dissemination, and diffu-sion research.

The AHA’s 2020 Goals include a new concept of cardiovas-cular health that directly incorporates metrics of lifestyle behav-

Artinian et al Promoting Physical Activity and Dietary Changes 433

iors, including diet and PA habits, as defining health.225 Whereasfurther research is needed on several aspects of individual- andgroup-based interventions to improve diet and PA, a sufficientevidence base now exists to incorporate several specific strat-

egies, as outlined in Table 4, into clinical practice. Thepromotion of these interventions should form a key com-ponent of strategies to achieve the AHA’s 2020 Goals andimprove the cardiovascular health of the population.

Disclosures

Writing Group Disclosures

Writing GroupMember Employment Research Grant Other Research Support

Speakers’Bureau/Honoraria

ExpertWitness

OwnershipInterest

Consultant/Advisory Board Other

Nancy T. Artinian Wayne StateUniversity

None None None None None None None

Gerald F.Fletcher

Mayo Clinic None None None None None None None

Philip A. Ades University ofVermont

None None None None None None None

JoAnne Banks Winston-SalemState

None None None None None None None

Kathy Berra Stanford University None None BoehringerIngelheim*; Gilead*

None None Knowledgepoint3602009 Lipids Online

ContributingAuthor*; AspirinMeasurementAdvisory Panel

NCQA/CPM/HEDIS2009*; NHLBI

ImplementationWorkshop 2009*

None

Lynne T. Braun Rush University None None None None None AHA LearningLibrary*; Heart

Profilers*

None

Lora E. Burke University ofPittsburgh

NIH† None Novo Nordisk* None None None None

J. Larry Durstine University of SouthCarolina

None None None None None None None

Linda J. Ewing University ofPittsburgh

NHLBI*; NIDDK*;NIH†; Pennsylvania

Tobacco Fund†

None None None None None None

Jerome L. Fleg NIH None None None None Bristol-MyersSquibb*

None None

Barbara J.Fletcher

University of NorthFlorida

None None None None None None Pritchett andHull Associates†

Laura L. Hayman University ofMassachusetts-

Boston

None None None None None None None

NancyHouston-Miller

Stanford University None None Gilead*; Pfizer*;Boehringer-Ingelheim*

None None None None

Suzanne Hughes Robinson MemorialHospital

None None None None None None Associate Editor,Cardiosource

(ACC)†

Laurie A. Kopin University ofRochester

None None Bristol-Myers Squibb*;Sanofi-Aventis*

None None None None

William E. Kraus Duke University None None None None None None None

PennyKris-Etherton

Penn StateUniversity

None California PistachioCommission†; General

Mills†; Hershey Foods†;National Cancer

Institute†; NationalCattlemen’s Beef

Association†; TomatoWellness Council†;Unilever†; United

Soybean Board†; USDepartment ofAgriculture†

None None None Health FitnessCorp*; Heinz*;

Merck*; ShapingAmerica Health*;

Unilever*

None

(Continued)

434 Circulation July 27, 2010

Reviewer Disclosures

Reviewer Employment Research Grant

OtherResearchSupport

Speakers’Bureau/

HonorariaExpert

WitnessOwnership

InterestConsultant/Advisory

Board Other

Vera Bittner University of Alabamaat Birmingham

NHLBI-HF ACTION Study(Multicenter Trial of

Exercise Training in HeartFailure)†

None American HeartAssociation*

None None None None

Timothy S. Church Pennington BiomedicalResearch Center

None None None None None None None

Barry Franklin William BeaumontHospital

None None None None None Smart Balance* None

Bonnie J. Spring NorthwesternUniversity

NIH† None None None None None None

This table represents the relationships of reviewers that may be perceived as actual or reasonably perceived conflicts of interest as reported on the DisclosureQuestionnaire, which all reviewers are required to complete and submit. A relationship is considered to be “significant” if (a) the person receives $10 000 or moreduring any 12 month period, or 5% or more of the person’s gross income; or (b) the person owns 5% or more of the voting stock or share of the entity, or owns$10 000 or more of the fair market value of the entity. A relationship is considered to be “modest” if it is less than “significant” under the preceding definition.

*Modest.†Significant.

Writing Group Disclosures, Continued

Writing GroupMember Employment Research Grant Other Research Support

Speakers’Bureau/Honoraria

ExpertWitness

OwnershipInterest

Consultant/Advisory Board Other

ShirikiKumanyika

University ofPennsylvania

None None None None None Weight Watchers,Inc*

None

Alice H.Lichtenstein

Tufts University None None None None None None None

Janet C.Meininger

University of TexasHealth ScienceCenter–Houston

NIH† None None None None Center for HealthPromotionResearch-

University of TexasSchool of Nursing

Austin, TX*

None

Todd D. Miller Mayo Clinic Lantheus MedicalImaging†;

Molecular InsightPharmaceuticals†

None None None None TherOx, Inc.*; TheMedicinesCompany*

None

DariushMozaffarian

Harvard University In discussions withSigma Tau,

GlaxoSmithKline,and Pronova for an

investigator-initiated trial of

fish oil and cardiacdisease

None None None None None None

Nancy S.Redeker

Yale University None None None None None None None

Eileen M.Stuart-Shor

University ofMassachusetts

Boston/Beth IsraelDeaconess Medical

Center

NIH† None None None None None None

Linda Van Horn NorthwesternUniversity

NIH† None None None None None None

This table represents the relationships of writing group members that may be perceived as actual or reasonably perceived conflicts of interest as reported on theDisclosure Questionnaire, which all members of the writing group are required to complete and submit. A relationship is considered to be “significant” if (a) the personreceives $10 000 or more during any 12-month period, or 5% or more of the person’s gross income; or (b) the person owns 5% or more of the voting stock or shareof the entity, or owns $10 000 or more of the fair market value of the entity. A relationship is considered to be “modest” if it is less than “significant” under thepreceding definition.

*Modest.†Significant.

Artinian et al Promoting Physical Activity and Dietary Changes 435

References1. Rosamond W, Flegal K, Furie K, Go A, Greenlund K, Haase N,

Hailpern SM, Ho M, Howard V, Kissela B, Kittner S, Lloyd-Jones D,McDermott M, Meigs J, Moy C, Nichol G, O’Donnell C, Roger V,Sorlie P, Steinberger J, Thom T, Wilson M, Hong Y; American HeartAssociation Statistics Committee and Stroke Statistics Subcommittee.Heart disease and stroke statistics—2008 update: a report from theAmerican Heart Association Statistics Committee and Stroke StatisticsSubcommittee. Circulation. 2008;117:e25–e146.

2. Hicks LS, Fairchild DG, Cook EF, Ayanian JZ. Association of region ofresidence and immigrant status with hypertension, renal failure, cardio-vascular disease, and stroke, among African-American participants inthe third National Health and Nutrition Examination Survey (NHANESIII). Ethn Dis. 2003;13:316–323.

3. Koya DL, Egede LE. Association between length of residence andcardiovascular disease risk factors among an ethnically diverse group ofUnited States immigrants. J Gen Intern Med. 2007;22:841–846.

4. Rothman AJ. Toward a theory-based analysis of behavioral mainte-nance. Health Psychol. 2000;19:64–69.

5. Anderson R. U.S. Decennial Life Tables for 1989–91, vol 1 no 4: UnitedStates Life Tables Eliminating Certain Causes of Death. Hyattsville,MD: National Center for Health Statistics; 1999.

6. Lloyd-Jones D, Adams R, Carnethon M, De Simone G, Ferguson TB,Flegal K, Ford E, Furie K, Go A, Greenlund K, Haase N, Hailpern S, HoM, Howard V, Kissela B, Kittner S, Lackland D, Lisabeth L, Marelli A,McDermott M, Meigs J, Mozaffarian D, Nichol G, O’Donnell C, RogerV, Rosamond W, Sacco R, Sorlie P, Stafford R, Steinberger J, Thom T,Wasserthiel-Smoller S, Wong N, Wylie-Rosett J, Hong Y; AmericanHeart Association Statistics Committee and Stroke Statistics Subcom-mittee. Heart disease and stroke statistics—2009 update: a report fromthe American Heart Association Statistics Committee and Stroke Sta-tistics Subcommittee. Circulation. 2009;119:480–486.

7. Smith SC Jr, Blair SN, Bonow RO, Brass LM, Cerqueira MD, DracupK, Fuster V, Gotto A, Grundy SM, Miller NH, Jacobs A, Jones D,Krauss RM, Mosca L, Ockene I, Pasternak RC, Pearson T, Pfeffer MA,Starke RD, Taubert KA. AHA/ACC guidelines for preventing heartattack and death in patients with atherosclerotic cardiovascular disease:2001 update: a statement for healthcare professionals from the AmericanHeart Association and the American College of Cardiology. J Am CollCardiol. 2001;38:1581–1583.

8. Thompson PD, Buchner D, Pina IL, Balady GJ, Williams MA, MarcusBH, Berra K, Blair SN, Costa F, Franklin B, Fletcher GF, Gordon NF,Pate RR, Rodriguez BL, Yancey AK, Wenger NK. Exercise andphysical activity in the prevention and treatment of atheroscleroticcardiovascular disease: a statement from the Council on Clinical Car-diology (Subcommittee on Exercise, Rehabilitation, and Prevention) andthe Council on Nutrition, Physical Activity, and Metabolism (Subcom-mittee on Physical Activity). Circulation. 2003;107:3109–3116.

9. Marcus BH, Williams DM, Dubbert PM, Sallis JF, King AC, YanceyAK, Franklin BA, Buchner D, Daniels SR, Claytor RP. Physical activityintervention studies: what we know and what we need to know: ascientific statement from the American Heart Association Council onNutrition, Physical Activity, and Metabolism (Subcommittee onPhysical Activity); Council on Cardiovascular Disease in the Young;and the Interdisciplinary Working Group on Quality of Care andOutcomes Research. Circulation. 2006;114:2739–2752.

10. Lichtenstein AH, Appel LJ, Brands M, Carnethon M, Daniels S, FranchHA, Franklin B, Kris-Etherton P, Harris WS, Howard B, Karanja N,Lefevre M, Rudel L, Sacks F, Van Horn L, Winston M, Wylie-Rosett J.Diet and lifestyle recommendations revision 2006: a scientific statementfrom the American Heart Association Nutrition Committee. Circulation.2006;114:82–96.

11. US Department of Health and Human Services and US Department ofAgriculture. Dietary Guidelines for Americans, 2005. 6th ed. Wash-ington, DC: US Government Printing Office; 2005.

12. Haskell WL, Lee IM, Pate RR, Powell KE, Blair SN, Franklin BA,Macera CA, Heath GW, Thompson PD, Bauman A. Physical activityand public health: updated recommendation for adults from theAmerican College of Sports Medicine and the American Heart Asso-ciation. Circulation. 2007;116:1081–1093.

13. US Centers for Disease Control and Prevention. Targeting Tobacco Useat a Glance 2008. Atlanta, GA: US Centers for Disease Control andPrevention; 2008.

14. Cohen J. Statistical Power Analysis for the Behavioral Sciences. 2nd ed.Hillsdale, NJ: Lawrence Erlbaum Associates; 1988.

15. Carels RA, Darby L, Cacciapaglia HM, Konrad K, Coit C, Harper J,Kaplar ME, Young K, Baylen CA, Versland A. Using motivationalinterviewing as a supplement to obesity treatment: a stepped-careapproach. Health Psychol. 2007;26:369–374.

16. Strecher VJ, Seijts GH, Kok GJ, Latham GP, Glasgow R, DeVellis B,Meertens RM, Bulger DW. Goal setting as a strategy for health behaviorchange. Health Educ Q. 1995;22:190–200.

17. Delichatsios HK, Friedman RH, Glanz K, Tennstedt S, Smigelski C,Pinto BM, Kelley H, Gillman MW. Randomized trial of a “talkingcomputer” to improve adults’ eating habits. Am J Health Promot. 2001;15:215–224.

18. Calfas KJ, Sallis JF, Zabinski MF, Wilfley DE, Rupp J, Prochaska JJ,Thompson S, Pratt M, Patrick K. Preliminary evaluation of a multicom-ponent program for nutrition and physical activity change in primarycare: PACE� for adults. Prev Med. 2002;34:153–161.

19. Burke BL, Arkowitz H, Menchola M. The efficacy of motivationalinterviewing: a meta-analysis of controlled clinical trials. J Consult ClinPsychol. 2003;71:843–861.

20. Bandura A. Self-Efficacy: The Exercise of Control. New York, NY:W.H. Freeman; 1997.

21. Bandura A. Health promotion from the perspective of social cognitivetheory. Psychol Health. 1998;13:623–649.

22. Timmerman GM. A concept analysis of intimacy. Issues Ment HealthNurs. 1991;12:19–30.

23. Carels RA, Darby LA, Cacciapaglia HM, Douglass OM. Reducingcardiovascular risk factors in postmenopausal women through a lifestylechange intervention. J Womens Health (Larchmt). 2004;13:412–426.

24. Burke LE, Styn MA, Steenkiste AR, Music E, Warziski M, Choo J. Arandomized clinical trial testing treatment preference and two dietaryoptions in behavioral weight management: preliminary results of theimpact of diet at 6 months: PREFER study. Obesity (Silver Spring).2006;14:2007–2017.

25. Jeffery RW, Wing RR, Thorson C, Burton LR. Use of personal trainersand financial incentives to increase exercise in a behavioral weight-lossprogram. J Consult Clin Psychol. 1998;66:777–783.

26. Appel LJ, Champagne CM, Harsha DW, Cooper LS, Obarzanek E,Elmer PJ, Stevens VJ, Vollmer WM, Lin PH, Svetkey LP, Stedman SW,Young DR; Writing Group of the PREMIER Collaborative ResearchGroup. Effects of comprehensive lifestyle modification on bloodpressure control: main results of the PREMIER clinical trial. JAMA.2003;289:2083–2093.

27. McManus K, Antinoro L, Sacks F. A randomized controlled trial of amoderate-fat, low-energy diet compared with a low fat, low-energy dietfor weight loss in overweight adults. Int J Obes Relat Metab Disord.2001;25:1503–1511.

28. Wadden TA, Berkowitz RI, Womble LG, Sarwer DB, Phelan S, CatoRK, Hesson LA, Osei SY, Kaplan R, Stunkard AJ. Randomized trial oflifestyle modification and pharmacotherapy for obesity. N Engl J Med.2005;353:2111–2120.

29. Wing RR, Jeffery RW. Benefits of recruiting participants with friendsand increasing social support for weight loss and maintenance. J ConsultClin Psychol. 1999;67:132–138.

30. Burke LE, Dunbar-Jacob J, Orchard TJ, Sereika SM. Improvingadherence to a cholesterol-lowering diet: a behavioral interventionstudy. Patient Educ Couns. 2005;57:134–142.

31. Green BB, McAfee T, Hindmarsh M, Madsen L, Caplow M, Buist D.Effectiveness of telephone support in increasing physical activity levelsin primary care patients. Am J Prev Med. 2002;22:177–183.

32. Stevens VJ, Glasgow RE, Toobert DJ, Karanja N, Smith KS. One-yearresults from a brief, computer-assisted intervention to decrease con-sumption of fat and increase consumption of fruits and vegetables. PrevMed. 2003;36:594–600.

33. Anderson ES, Winett RA, Wojcik JR, Winett SG, Bowden T. A com-puterized social cognitive intervention for nutrition behavior: direct andmediated effects on fat, fiber, fruits, and vegetables, self-efficacy, andoutcome expectations among food shoppers. Ann Behav Med. 2001;23:88–100.

34. Napolitano MA, Fotheringham M, Tate D, Sciamanna C, Leslie E,Owen N, Bauman A, Marcus B. Evaluation of an Internet-based physicalactivity intervention: a preliminary investigation. Ann Behav Med. 2003;25:92–99.

35. Micco N, Gold B, Buzzell P, Leonard H, Pintauro S, Harvey-Berino J.Minimal in-person support as an adjunct to internet obesity treatment.Ann Behav Med. 2007;33:49–56.

436 Circulation July 27, 2010

36. Tate DF, Jackvony EH, Wing RR. Effects of Internet behavioral coun-seling on weight loss in adults at risk for type 2 diabetes: a randomizedtrial. JAMA. 2003;289:1833–1836.

37. Wylie-Rosett J, Swencionis C, Ginsberg M, Cimino C, Wassertheil-Smoller S, Caban A, Segal-Isaacson CJ, Martin T, Lewis J. Comput-erized weight loss intervention optimized staff time: the clinical and costresults of a controlled clinical trial conducted in a managed care setting.J Am Diet Assoc. 2001;101:1155–1162.

38. Knowler WC, Barrett-Connor E, Fowler SE, Hamman RF, Lachin JM,Walker EA, Nathan DM; Diabetes Prevention Program Research Group.Reduction in the incidence of type 2 diabetes with lifestyle interventionor metformin. N Engl J Med. 2002;346:393–403.

39. Glasgow RE, La Chance PA, Toobert DJ, Brown J, Hampson SE, RiddleMC. Long-term effects and costs of brief behavioural dietary inter-vention for patients with diabetes delivered from the medical office.Patient Educ Couns. 1997;32:175–184.

40. Perry CK, Rosenfeld AG, Bennett JA, Potempa K. Heart-to-Heart:promoting walking in rural women through motivational interviewingand group support. J Cardiovasc Nurs. 2007;22:304–312.

41. Stevens VJ, Obarzanek E, Cook NR, Lee IM, Appel LJ, Smith West D,Milas NC, Mattfeldt-Beman M, Belden L, Bragg C, Millstone M, Rac-zynski J, Brewer A, Singh B, Cohen J; Trials for the HypertensionPrevention Research Group. Long-term weight loss and changes inblood pressure: results of the Trials of Hypertension Prevention, phaseII. Ann Intern Med. 2001;134:1–11.

42. 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.

43. McNabb W, Quinn M, Kerver J, Cook S, Karrison T. The PATHWAYSchurch-based weight loss program for urban African-American womenat risk for diabetes. Diabetes Care. 1997;20:1518–1523.

44. Eakin EG, Bull SS, Riley KM, Reeves MM, McLaughlin P, Gutierrez S.Resources for health: A primary-care-based diet and physical activityintervention targeting urban Latinos with multiple chronic conditions.Health Psychol. 2007;26:392–400.

45. Jacobs AD, Ammerman AS, Ennett ST, Campbell MK, Tawney KW,Aytur SA, Marshall SW, Will JC, Rosamond WD. Effects of a tailoredfollow-up intervention on health behaviors, beliefs, and attitudes.J Womens Health (Larchmt). 2004;13:557–568.

46. Albright CL, Pruitt L, Castro C, Gonzalez A, Woo S, King AC. Mod-ifying physical activity in a multiethnic sample of low-income women:one-year results from the IMPACT (Increasing Motivation for PhysicalACTivity) project. Ann Behav Med. 2005;30:191–200.

47. Coates RJ, Bowen DJ, Kristal AR, Feng Z, Oberman A, Hall WD,George V, Lewis CE, Kestin M, Davis M, Evans M, Grizzle JE, CliffordCK. The Women’s Health Trial Feasibility Study in Minority Popu-lations: changes in dietary intakes. Am J Epidemiol. 1999;149(12):1104–1112.

48. Havas S, Anliker J, Damron D, Langenberg P, Ballesteros M, FeldmanR. Final results of the Maryland WIC 5-A-Day Promotion Program.Am J Public Health. 1998;88:1161–1167.

49. Keyserling TC, Samuel-Hodge CD, Ammerman AS, Ainsworth BE,Henrıquez-Roldan CF, Elasy TA, Skelly AH, Johnston LF, BangdiwalaSI. A randomized trial of an intervention to improve self-care behaviorsof African-American women with type 2 diabetes: impact on physicalactivity. Diabetes Care. 2002;25:1576–1583.

50. Mayer-Davis EJ, D’Antonio AM, Smith SM, Kirkner G, Levin Martin S,Parra-Medina D, Schultz R. Pounds off with empowerment (POWER):a clinical trial of weight management strategies for black and whiteadults with diabetes who live in medically underserved rural commu-nities. Am J Public Health. 2004;94:1736–1742.

51. Racette SB, Weiss EP, Obert KA, Kohrt WM, Holloszy JO. Modestlifestyle intervention and glucose tolerance in obese African Americans.Obes Res. 2001;9:348–355.

52. Rosal MC, Olendzki B, Reed GW, Gumieniak O, Scavron J, Ockene I.Diabetes self-management among low-income Spanish-speakingpatients: a pilot study. Ann Behav Med. 2005;29:225–235.

53. Staten LK, Gregory-Mercado KY, Ranger-Moore J, Will JC, GiulianoAR, Ford ES, Marshall J. Provider counseling, health education, andcommunity health workers: the Arizona WISEWOMAN project.J Womens Health (Larchmt). 2004;13:547–556.

54. Howard-Pitney B, Winkleby MA, Albright CL, Bruce B, Fortmann SP.The Stanford Nutrition Action Program: a dietary fat intervention forlow-literacy adults. Am J Public Health. 1997;87:1971–1976.

55. Yanek LR, Becker DM, Moy TF, Gittelsohn J, Koffman DM. ProjectJoy: faith based cardiovascular health promotion for African Americanwomen. Public Health Rep. 2001;116(suppl 1):68–81.

56. Andersen RE, Wadden TA, Bartlett SJ, Zemel B, Verde TJ, FranckowiakSC. Effects of lifestyle activity vs structured aerobic exercise in obesewomen: a randomized trial. JAMA. 1999;281:335–340.

57. Tate DF, Jackvony EH, Wing RR. A randomized trial comparing humane-mail counseling, computer-automated tailored counseling, and nocounseling in an Internet weight loss program. Arch Intern Med. 2006;166:1620–1625.

58. Howard BV, Van Horn L, Hsia J, Manson JE, Stefanick ML,Wassertheil-Smoller S, Kuller LH, LaCroix AZ, Langer RD, Lasser NL,Lewis CE, Limacher MC, Margolis KL, Mysiw WJ, Ockene JK, ParkerLM, Perri MG, Phillips L, Prentice RL, Robbins J, Rossouw JE, SartoGE, Schatz IJ, Snetselaar LG, Stevens VJ, Tinker LF, Trevisan M,Vitolins MZ, Anderson GL, Assaf AR, Bassford T, Beresford SA, BlackHR, Brunner RL, Brzyski RG, Caan B, Chlebowski RT, Gass M, GranekI, Greenland P, Hays J, Heber D, Heiss G, Hendrix SL, Hubbell FA,Johnson KC, Kotchen JM. Low-fat dietary pattern and risk of cardio-vascular disease: the Women’s Health Initiative Randomized ControlledDietary Modification Trial. JAMA. 2006;295:655–666.

59. Yancey AK, McCarthy WJ, Harrison GG, Wong WK, Siegel JM, LeslieJ. Challenges in improving fitness: results of a community-based, ran-domized, controlled lifestyle change intervention. J Womens Health(Larchmt). 2006;15:412–429.

60. Butryn ML, Phelan S, Hill JO, Wing RR. Consistent self-monitoring ofweight: a key component of successful weight loss maintenance. Obesity(Silver Spring). 2007;15:3091–3096.

61. Baker RC, Kirschenbaum DS. Weight control during the holidays:highly consistent self-monitoring as a potentially useful copingmechanism. Health Psychol. 1998;17:367–370.

62. Burke LE, Sereika SM, Music E, Warziski M, Styn MA, Stone A. Usinginstrumented paper diaries to document self-monitoring patterns inweight loss. Contemp Clin Trials. 2008;29:182–193.

63. Hollis JF, Gullion CM, Stevens VJ, Brantley PJ, Appel LJ, Ard JD,Champagne CM, Dalcin A, Erlinger TP, Funk K, Laferriere D, Lin PH,Loria CM, Samuel-Hodge C, Vollmer WM, Svetkey LP; Weight LossMaintenance Trial Research Group. Weight loss during the intensiveintervention phase of the weight-loss maintenance trial. Am J Prev Med.2008;35:118–126.

64. Tinker LF, Rosal MC, Young AF, Perri MG, Patterson RE, Van Horn L,Assaf AR, Bowen DJ, Ockene J, Hays J, Wu L. Predictors of dietarychange and maintenance in the Women’s Health Initiative Dietary Mod-ification Trial. J Am Diet Assoc. 2007;107:1155–1166.

65. Conn VS, Valentine JC, Cooper HM. Interventions to increase physicalactivity among aging adults: a meta-analysis. Ann Behav Med. 2002;24:190–200.

66. Simkin-Silverman LR, Wing RR, Boraz MA, Kuller LH. Lifestyleintervention can prevent weight gain during menopause: results from a5-year randomized clinical trial. Ann Behav Med. 2003;26:212–220.

67. Toobert DJ, Strycker LA, Glasgow RE, Barrera M Jr, Angell K. Effectsof the Mediterranean lifestyle program on multiple risk behaviors andpsychosocial outcomes among women at risk for heart disease. AnnBehav Med. 2005;29:128–137.

68. Yeh MC, Rodriguez E, Nawaz H, Gonzalez M, Nakamoto D, Katz DL.Technical skills for weight loss: 2-y follow-up results of a randomizedtrial. Int J Obes Relat Metab Disord. 2003;27:1500–1506.

69. Marcus BH, Napolitano MA, King AC, Lewis BA, Whiteley JA,Albrecht A, Parisi A, Bock B, Pinto B, Sciamanna C, Jakicic J, Papan-donatos GD. Telephone versus print delivery of an individualized moti-vationally tailored physical activity intervention: Project STRIDE.Health Psychol. 2007;26:401–409.

70. Boulware LE, Cooper LA, Ratner LE, LaVeist TA, Powe NR. Race andtrust in the health care system. Public Health Rep. 2003;118:358–365.

71. Elliot DL, Goldberg L, Kuehl KS, Moe EL, Breger RK, Pickering MA.The PHLAME (Promoting Healthy Lifestyles: Alternative Models’Effects) firefighter study: outcomes of two models of behavior change.J Occup Environ Med. 2007;49:204–213.

72. Wadden TA, Vogt RA, Foster GD, Anderson DA. Exercise and themaintenance of weight loss: 1-year follow-up of a controlled clinicaltrial. J Consult Clin Psychol. 1998;66:429–433.

73. Glanz K, Oldenburg B. Utilizing theories and constructs across modelsof behavior change. In: Patterson R, ed. Changing Patient Behavior:Improving Outcomes in Health and Disease Management. SanFrancisco, Calif: Jossey-Bass; 2001:25–40.

Artinian et al Promoting Physical Activity and Dietary Changes 437

74. Buller DB, Morrill C, Taren D, Aickin M, Sennott-Miller L, Buller MK,Larkey L, Alatorre C, Wentzel TM. Randomized trial testing the effectof peer education at increasing fruit and vegetable intake. J Natl CancerInst. 1999;91:1491–1500.

75. Kumanyika SK, Adams-Campbell L, Van Horn B, Ten Have TR, TreuJA, Askov E, Williams J, Achterberg C, Zaghloul S, Monsegu D, BrightM, Stoy DB, Malone-Jackson M, Mooney D, Deiling S, Caulfield J.Outcomes of a cardiovascular nutrition counseling program in African-Americans with elevated blood pressure or cholesterol level. J Am DietAssoc. 1999;99:1380–1391.

76. Campbell MK, Demark-Wahnefried W, Symons M, Kalsbeek WD,Dodds J, Cowan A, Jackson B, Motsinger B, Hoben K, Lashley J,Demissie S, McClelland JW. Fruit and vegetable consumption andprevention of cancer: the Black Churches United for Better Healthproject. Am J Public Health. 1999;89:1390–1396.

77. Patterson R. The new focus: Integrating behavioral science into diseasemanagement. In: Patterson R, ed. Changing Patient Behavior:Improving Outcomes in Health and Disease Management. SanFrancisco, Calif: Jossey-Bass; 2001:1–21.

78. Grant L, Evans A. Principles of Behavioral Analysis. New York: HarperCollins; 1994.

79. Marcus BH, Bock BC, Pinto BM, Forsyth LH, Roberts MB, TraficanteRM. Efficacy of an individualized, motivationally-tailored physicalactivity intervention. Ann Behav Med. 1998;20:174–180.

80. Glasgow RE, Toobert DJ. Brief, computer-assisted diabetes dietaryself-management counseling: effects on behavior, physiologicoutcomes, and quality of life. Med Care. 2000;38:1062–1103.

81. Fries E, Edinboro P, McClish D, Manion L, Bowen D, Beresford SA,Ripley J. Randomized trial of a low-intensity dietary intervention inrural residents: the Rural Physician Cancer Prevention Project. Am JPrev Med. 2005;28:162–168.

82. Bandura A. Self-efficacy. In: Social Foundations of Thought andAction: A Social Cognitive Theory. Englewood Cliffs, NJ: Prentice-Hall;1986:390–453.

83. Ewart CK, Stewart KJ, Gillilan RE, Kelemen MH, Valenti SA, ManleyJD, Kelemen MD. Usefulness of self-efficacy in predicting overexertionduring programmed exercise in coronary artery disease. Am J Cardiol.1986;57:557–561.

84. Hagler AS, Norman GJ, Zabinski MF, Sallis JF, Calfas KJ, Patrick K.Psychosocial correlates of dietary intake among overweight and obesemen. Am J Health Behav. 2007;31:3–12.

85. Henry H, Reimer K, Smith C, Reicks M. Associations of decisionalbalance, processes of change, and self-efficacy with stages of change forincreased fruit and vegetable intake among low-income, African-American mothers. J Am Diet Assoc. 2006;106:841–849.

86. Linde JA, Rothman AJ, Baldwin AS, Jeffery RW. The impact of self-efficacy on behavior change and weight change among overweightparticipants in a weight loss trial. Health Psychol. 2006;25:282–291.

87. Nelson KM, McFarland L, Reiber G. Factors influencing disease self-management among veterans with diabetes and poor glycemic control.J Gen Intern Med. 2007;22:442–447.

88. Richman RM, Loughnan GT, Droulers AM, Steinbeck KS, Caterson ID.Self-efficacy in relation to eating behaviour among obese and non-obesewomen. Int J Obes Relat Metab Disord. 2001;25:907–913.

89. Schwarzer R, Renner B. Social-cognitive predictors of health behavior:action self-efficacy and coping self-efficacy. Health Psychol. 2000;19:487–495.

90. Taylor CB, Bandura A, Ewart CK, Miller NH, DeBusk RF. Exercisetesting to enhance wives’ confidence in their husbands’ cardiac capa-bility soon after clinically uncomplicated acute myocardial infarction.Am J Cardiol. 1985;55:635–638.

91. Taylor CB, Houston-Miller N, Killen JD, DeBusk RF. Smoking ces-sation after acute myocardial infarction: effects of a nurse-managedintervention. Ann Intern Med. 1990;113:118–123.

92. Van Duyn MA, Kristal AR, Dodd K, Campbell MK, Subar AF, StablesG, Nebeling L, Glanz K. Association of awareness, intrapersonal andinterpersonal factors, and stage of dietary change with fruit and veg-etable consumption: a national survey. Am J Health Promot. 2001;16:69–78.

93. Ahluwalia JS, Nollen N, Kaur H, James AS, Mayo MS, Resnicow K.Pathway to health: cluster-randomized trial to increase fruit and veg-etable consumption among smokers in public housing. Health Psychol.2007;26:214–221.

94. Linnan L, Bowling M, Childress J, Lindsay G, Blakey C, Pronk S,Wieker S, Royall P. Results of the 2004 National Worksite HealthPromotion Survey. Am J Public Health. 2008;98:1503–1509.

95. Ockene IS, Hebert JR, Ockene JK, Saperia GM, Stanek E, Nicolosi R,Merriam PA, Hurley TG. Effect of physician-delivered nutrition coun-seling training and an office-support program on saturated fat intake,weight, and serum lipid measurements in a hyperlipidemic population:Worcester Area Trial for Counseling in Hyperlipidemia (WATCH).Arch Intern Med. 1999;159:725–731.

96. Hartman TJ, McCarthy PR, Park RJ, Schuster E, Kushi LH. Results ofa community-based low-literacy nutrition education program. J Com-munity Health. 1997;22:325–341.

97. D’Zurilla T, Nezu AM. Social Problem Solving in Adults. New York:Academic Press; 1998.

98. Ammerman AS, Keyserling TC, Atwood JR, Hosking JD, Zayed H,Krasny C. A randomized controlled trial of a public health nurse directedtreatment program for rural patients with high blood cholesterol. PrevMed. 2003;36:340–351.

99. Rollnick S, Miller WR. What is motivational interviewing? Behav CognPsychother. 1995;23:325–334.

100. Miller WR, Benefield RG, Tonigan JS. Enhancing motivation forchange in problem drinking: a controlled comparison of two therapiststyles. J Consult Clin Psychol. 1993;61:455–461.

101. Rollnick S, Miller W, Butler C. Motivational Interviewing in HealthCare. New York, NY: Guilford Press; 2008.

102. Resnicow K, Jackson A, Wang T, De AK, McCarty F, Dudley WN,Baranowski T. A motivational interviewing intervention to increase fruitand vegetable intake through black churches: results of the Eat for Lifetrial. Am J Public Health. 2001;91:1686–1693.

103. Resnicow K, Jackson A, Blissett D, Wang T, McCarty F, Rahotep S,Periasamy S. Results of the healthy body healthy spirit trial. HealthPsychol. 2005;24:339–348.

104. Richards A, Kattelmann KK, Ren C. Motivating 18- to 24-year-olds toincrease their fruit and vegetable consumption. J Am Diet Assoc. 2006;106:1405–1411.

105. Knight KM, McGowan L, Dickens C, Bundy C. A systematic review ofmotivational interviewing in physical health care settings. Br J HealthPsychol. 2006;11:319–332.

106. Hyman DJ, Pavlik VN, Taylor WC, Goodrick GK, Moye L. Simulta-neous vs sequential counseling for multiple behavior change. ArchIntern Med. 2007;167:1152–1158.

107. Butterworth S, Linden A, McClay W, Leo MC. Effect of motivationalinterviewing-based health coaching on employees’ physical and mentalhealth status. J Occup Health Psychol. 2006;11:358–365.

108. Marcus BH, Lewis BA, Williams DM, Dunsiger S, Jakicic JM, WhiteleyJA, Albrecht AE, Napolitano MA, Bock BC, Tate DF, Sciamanna CN,Parisi AF. A comparison of Internet and print-based physical activityinterventions. Arch Intern Med. 2007;167:944–949.

109. Jakicic JM, Winters C, Lang W, Wing RR. Effects of intermittentexercise and use of home exercise equipment on adherence, weight loss,and fitness in overweight women: a randomized trial. JAMA. 1999;282:1554–1560.

110. Elder JP, Candelaria J, Woodruff SI, Golbeck AL, Criqui MH, TalaveraGA, Rupp JW, Domier CP. Initial results of ‘Language for Health’:cardiovascular disease nutrition education for English-as-a-second-language students. Health Educ Res. 1998;13:567–575.

111. Look AHEAD Research Group, Pi-Sunyer X, Blackburn G, BrancatiFL, Bray GA, Bright R, Clark JM, Curtis JM, Espeland MA, Foreyt JP,Graves K, Haffner SM, Harrison B, Hill JO, Horton ES, Jakicic J,Jeffery RW, Johnson KC, Kahn S, Kelley DE, Kitabchi AE, KnowlerWC, Lewis CE, Maschak-Carey BJ, Montgomery B, Nathan DM,Patricio J, Peters A, Redmon JB, Reeves RS, Ryan DH, Safford M, VanDorsten B, Wadden TA, Wagenknecht L, Wesche-Thobaben J, WingRR, Yanovski SZ. Reduction in weight and cardiovascular disease riskfactors in individuals with type 2 diabetes: one-year results of the lookAHEAD trial. Diabetes Care. 2007;30:1374–1383.

112. Stoddard AM, Palombo R, Troped PJ, Sorensen G, Will JC. Cardio-vascular disease risk reduction: the Massachusetts WISEWOMAN proj-ect. J Womens Health (Larchmt). 2004;13:539–546.

113. Aldana SG, Greenlaw RL, Diehl HA, Salberg A, Merrill RM, OhmineS, Thomas C. The behavioral and clinical effects of therapeutic lifestylechange on middle-aged adults. Prev Chronic Dis. 2006;3:A05.

114. Spring B, Pagoto S, Pingitore R, Doran N, Schneider K, Hedeker D.Randomized controlled trial for behavioral smoking and weight control

438 Circulation July 27, 2010

treatment: effect of concurrent versus sequential intervention. J ConsultClin Psychol. 2004;72:785–796.

115. Vandelanotte C, De Bourdeaudhuij I, Sallis JF, Spittaels H, Brug J.Efficacy of sequential or simultaneous interactive computer-tailoredinterventions for increasing physical activity and decreasing fat intake.Ann Behav Med. 2005;29:138–146.

116. Vandelanotte C, Reeves MM, Brug J, De Bourdeaudhuij I. A ran-domized trial of sequential and simultaneous multiple behavior changeinterventions for physical activity and fat intake. Prev Med. 2008;46:232–237.

117. Vandelanotte C, De Bourdeaudhuij I, Brug J. Two-year follow-up ofsequential and simultaneous interactive computer-tailored interventionsfor increasing physical activity and decreasing fat intake. Ann BehavMed. 2007;33:213–219.

118. Hunt JS, Siemienczuk J, Touchette D, Payne N. Impact of educationalmailing on the blood pressure of primary care patients with mild hyper-tension. J Gen Intern Med. 2004;19:925–930.

119. Yancey AK, McCarthy WJ, Taylor WC, Merlo A, Gewa C, Weber MD,Fielding JE. The Los Angeles Lift Off: a sociocultural environmentalchange intervention to integrate physical activity into the workplace.Prev Med. 2004;38:848–856.

120. Ledikwe JH, Rolls BJ, Smiciklas-Wright H, Mitchell DC, Ard JD,Champagne C, Karanja N, Lin PH, Stevens VJ, Appel LJ. Reductions indietary energy density are associated with weight loss in overweight andobese participants in the PREMIER trial. Am J Clin Nutr. 2007;85:1212–1221.

121. Jeffery RW, Drewnowski A, Epstein LH, Stunkard AJ, Wilson GT,Wing RR, Hill DR. Long-term maintenance of weight loss: currentstatus. Health Psychol. 2000;19(suppl):5–16.

122. Gold BC, Burke S, Pintauro S, Buzzell P, Harvey-Berino J. Weight losson the web: A pilot study comparing a structured behavioral interventionto a commercial program. Obesity (Silver Spring). 2007;15:155–164.

123. Heshka S, Anderson JW, Atkinson RL, Greenway FL, Hill JO, PhinneySD, Kolotkin RL, Miller-Kovach K, Pi-Sunyer FX. Weight loss withself-help compared with a structured commercial program: a ran-domized trial. JAMA. 2003;289:1792–1798.

124. Heshka S, Greenway F, Anderson JW, Atkinson RL, Hill JO, PhinneySD, Miller-Kovach K, Xavier Pi-Sunyer F. Self-help weight loss versusa structured commercial program after 26 weeks: a randomized con-trolled study. Am J Med. 2000;109:282–287.

125. Pinto BM, Goldstein MG, Ashba J, Sciamanna CN, Jette A. Randomizedcontrolled trial of physical activity counseling for older primary carepatients. Am J Prev Med. 2005;29:247–255.

126. van der Bij AK, Laurant MG, Wensing M. Effectiveness of physicalactivity interventions for older adults: a review. Am J Prev Med. 2002;22:120–133.

127. DeBusk RF, Miller NH, Superko HR, Dennis CA, Thomas RJ, Lew HT,Berger WE 3rd, Heller RS, Rompf J, Gee D, Kraemer HC, Bandura A,Ghandour G, Clark M, Shah RV, Fisher L, Taylor CB. A case-management system for coronary risk factor modification after acutemyocardial infarction. Ann Intern Med. 1994;120:721–729.

128. Haskell WL, Alderman EL, Fair JM, Maron DJ, Mackey SF, SuperkoHR, Williams PT, Johnstone IM, Champagne MA, Krauss RM,Farquhar JW. Effects of intensive multiple risk factor reduction oncoronary artherosclerosis and clinical cardiac events in men and womenwith coronary artery disease: the Stanford Coronary Risk InterventionProject (SCRIP). Circulation. 1994;89:975–990.

129. Wood DA, Kotseva K, Connolly S, Jennings C, Mead A, Jones J, HoldenA, De Bacquer D, Collier T, De Backer G, Faergeman O; EUROACTIONStudy Group. Nurse-coordinated mulitidisciplinary, family-based cardio-vascular disease prevention programme (EUROACTION) for patients withcoronary heart disease and asymptomatic individuals at high risk of cardio-vascular disease: a paired, cluster-randomized controlled trial. Lancet. 2008;371:1999–2912.

130. Delichatsios HK, Hunt MK, Lobb R, Emmons K, Gillman MW.EatSmart: efficacy of a multifaceted preventive nutrition intervention inclinical practice. Prev Med. 2001;33:91–98.

131. Griffiths F, Lindenmeyer A, Powell J, Lowe P, Thorogood M. Why arehealth care interventions delivered over the Internet? A systematicreview of published literature. J Med Internet Res. 2006;8:e10.

132. Pinto BM, Friedman R, Marcus BH, Kelley H, Tennstedt S, GillmanMW. Effects of a computer-based, telephone-counseling system onphysical activity. Am J Prev Med. 2002;23:113–120.

133. Birru MS, Monaco VM, Charles L, Drew H, Njie V, Bierria T, DetlefsenE, Steinman RA. Internet usage by low-literacy adults seeking healthinformation: an observational analysis. J Med Internet Res. 2004;6:e25.

134. Wathen CN, Harris RM. “I try to take care of it myself.” How ruralwomen search for health information. Qual Health Res. 2007;17:639–651.

135. Writing Group for the Activity Counseling Trial Research Group.Effects of physical activity counseling in primary care: the ActivityCounseling Trial: A randomized controlled trial. JAMA. 2001;286:677–687.

136. Sloane BC, Zimmer CG. The power of peer health education. J Am CollHealth. 1993;41:241–245.

137. Jackson EJ, Parks CP. Recruitment and training issues from selected layhealth advisor programs among African Americans: a 20-year per-spective. Health Educ Behav. 1997;24:418–431.

138. Eng E, Parker E, Harlan C. Lay health advisor intervention strategies: acontinuum from natural helping to paraprofessional helping. HealthEduc Behav. 1997;24:413–417.

139. Hausmann LR, Jeong K, Bost JE, Ibrahim SA. Perceived discriminationin health care and health status in a racially diverse sample. Med Care.2008;46:905–914.

140. Gamble VN. Under the shadow of Tuskegee: African Americans andhealth care. Am J Public Health. 1997;87:1773–1778.

141. Doescher MP, Saver BG, Franks P, Fiscella K. Racial and ethnicdisparities in perceptions of physician style and trust. Arch Fam Med.2007;9:1156–1163.

142. Frankish C, Lovato C, Shannon W. Models, theories, and priniciples ofhealth promotion with multicultural populations. In: Huff R, Kline M,eds. Promoting Health in Multicultural Populations: A Handbook forPractitioners. Thousand Oaks, Calif: Sage; 1999:41–72.

143. Chen JL. Culturally competent health care. Public Health Rep. 2000;115:25–33.

144. Elder JP, Ayala GX, Campbell NR, Arredondo EM, Slymen DJ,Baquero B, Zive M, Ganiats TG, Engelberg M. Long-term effects of acommunication intervention for Spanish-dominant Latinas. Am J PrevMed. 2006;31:159–166.

145. Murphy PW, Davis TC, Mayeaux EJ, Sentell T, Arnold C, Rebouche C.Teaching nutrition education in adult learning centers: linking literacy,health care, and the community. J Community Health Nurs. 1996;13:149–158.

146. Doak C, Doak D, Root JH. Teaching Patients With Low Literacy Skills.2nd ed. Philadelphia, Pa: J. B. Lippincott; 1996.

147. Wang MC, Kim S, Gonzalez AA, MacLeod KE, Winkleby MA. Socio-economic and food-related physical characteristics of the neighbourhoodenvironment are associated with body mass index. J Epidemiol Com-munity Health. 2007;61:491–498.

148. Johnson CS, Garcia AC. Dietary and activity profiles of selectedimmigrant older adults in Canada. J Nutr Elder. 2003;23:23–39.

149. George GC, Milani TJ, Hanss-Nuss H, Freeland-Graves JH. Compliancewith dietary guidelines and relationship to psychosocial factors in low-income women in late postpartum. J Am Diet Assoc. 2005;105:916–926.

150. Dye CJ, Cason KL. Perceptions of older, low-income women aboutincreasing intake of fruits and vegetables. J Nutr Elder. 2005;25:21–41.

151. van Lenthe FJ, Brug J, Mackenbach JP. Neighbourhood inequalities inphysical inactivity: the role of neighbourhood attractiveness, proximityto local facilities and safety in the Netherlands. Soc Sci Med. 2005;60:763–775.

152. Palmeri D, Auld GW, Taylor T, Kendall P, Anderson J. Multipleperspectives on nutrition education needs of low-income Hispanics.J Community Health. 1998;23:301–316.

153. Lopez RP, Hynes HP. Obesity, physical activity, and the urban envi-ronment: public health research needs. Environ Health. 2006;5:25.

154. Estabrooks PA, Lee RE, Gyurcsik NC. Resources for physical activityparticipation: does availability and accessibility differ by neighborhoodsocioeconomic status? Ann Behav Med. 2003;25:100–104.

155. Powell LM, Slater S, Chaloupka FJ, Harper D. Availability of physicalactivity-related facilities and neighborhood demographic and socio-economic characteristics: a national study. Am J Public Health. 2006;96:1676–1680.

156. Smith WE, Day RS, Brown LB. Heritage retention and bean intakecorrelates to dietary fiber intakes in Hispanic mothers–Que SabrosaVida. J Am Diet Assoc. 2005;105:404–411.

157. Barnes DM, Almasy N. Refugees’ perceptions of healthy behaviors.J Immigr Health. 2005;7:185–193.

Artinian et al Promoting Physical Activity and Dietary Changes 439

158. Rothman A, Baldwin A, Hertel A. Self-regulation and behavior change:Disentangling behavioral initiation and behavioral maintenance. In:Vohs KD, Baumeister RF, eds. The Handbook of Self-Regulation:Research, Theory, and Applications. New York, NY: Guilford Press;2004:130–148.

159. Margetts BM, Thompson RL, Speller V, McVey D. Factors whichinfluence ‘healthy’ eating patterns: results from the 1993 Health Edu-cation Authority health and lifestyle survey in England. Public HealthNutr. 1998;1:193–198.

160. Stables GJ, Subar AF, Patterson BH, Dodd K, Heimendinger J, VanDuyn MA, Nebeling L. Changes in vegetable and fruit consumption andawareness among US adults: results of the 1991 and 1997 5 A Day forBetter Health Program surveys. J Am Diet Assoc. 2002;102:809–817.

161. Wu SJ, Chang YH, Wei IL, Kao MD, Lin YC, Pan WH. Intake levelsand major food sources of energy and nutrients in the Taiwanese elderly.Asia Pac J Clin Nutr. 2005;14:211–220.

162. Steptoe A, Doherty S, Kerry S, Rink E, Hilton S. Sociodemographic andpsychological predictors of changes in dietary fat consumption in adultswith high blood cholesterol following counseling in primary care.Health Psychol. 2000;19:411–419.

163. Howarth NC, Huang TT, Roberts SB, Lin BH, McCrory MA. Eatingpatterns and dietary composition in relation to BMI in younger and olderadults. Int J Obes (Lond). 2007;31:675–684.

164. Booth ML, Bauman A, Owen N, Gore CJ. Physical activity preferences,preferred sources of assistance, and perceived barriers to increasedactivity among physically inactive Australians. Prev Med. 1997;26:131–137.

165. Booth ML, Owen N, Bauman A, Clavisi O, Leslie E. Social-cognitiveand perceived environment influences associated with physical activityin older Australians. Prev Med. 2000;31:15–22.

166. Steffen LM, Arnett DK, Blackburn H, Shah G, Armstrong C, LuepkerRV, Jacobs DR Jr. Population trends in leisure-time physical activity:Minnesota Heart Survey, 1980–2000. Med Sci Sports Exerc. 2006;38:1716–1723.

167. Crespo CJ, Ainsworth BE, Keteyian SJ, Heath GW, Smit E. Prevalenceof physical inactivity and its relation to social class in U.S. adults: resultsfrom the Third National Health and Nutrition Examination Survey,1988–1994. Med Sci Sports Exerc. 1999;31:1821–1827.

168. Simons-Morton DG, Hogan P, Dunn AL, Pruitt L, King AC, Levine BD,Miller ST. Characteristics of inactive primary care patients: baselinedata from the activity counseling trial. For the Activity Counseling TrialResearch Group. Prev Med. 2000;31:513–521.

169. Dynesen AW, Haraldsdottir J, Holm L, Astrup A. Sociodemographicdifferences in dietary habits described by food frequency questions:results from Denmark. Eur J Clin Nutr. 2003;57:1586–1597.

170. Milligan RA, Burke V, Beilin LJ, Dunbar DL, Spencer MJ, Balde E,Gracey MP. Influence of gender and socio-economic status on dietarypatterns and nutrient intakes in 18-year-old Australians. Aust N Z JPublic Health. 1998;22:485–493.

171. Nasreddine L, Hwalla N, Sibai A, Hamze M, Parent-Massin D. Foodconsumption patterns in an adult urban population in Beirut, Lebanon.Public Health Nutr. 2006;9:194–203.

172. Hart A Jr, Tinker L, Bowen DJ, Longton G, Beresford SA. Correlates offat intake behaviors in participants in the eating for a healthy life study.J Am Diet Assoc. 2006;106:1605–1613.

173. Forshee RA, Storey ML. Demographics, not beverage consumption, isassociated with diet quality. Int J Food Sci Nutr. 2006;57:494–511.

174. Satia JA, Galanko JA, Neuhouser ML. Food nutrition label use isassociated with demographic, behavioral, and psychosocial factors anddietary intake among African Americans in North Carolina. J Am DietAssoc. 2005;105:392–402.

175. Norman A, Bellocco R, Vaida F, Wolk. Total physical activity inrelation to age, body mass, health and other factors in a cohort ofSwedish men. Int J Obes Relat Metab Disord. 2002;26:670–675.

176. Ainsworth BE, Wilcox S, Thompson WW, Richter DL, Henderson KA.Personal, social, and physical environmental correlates of physicalactivity in African-American women in South Carolina. Am J Prev Med.2003;25(suppl 1):23–29.

177. Ahmed NU, Smith GL, Flores AM, Pamies RJ, Mason HR, Woods KF,Stain SC. Racial/ethnic disparity and predictors of leisure-time physicalactivity among U.S. men. Ethn Dis. 2005;15:40–52.

178. Prochaska JO, DiClemente CC, Norcross JC. In search of how peoplechange: applications to addictive behaviors. Am Psychol. 1992;47:1102–1114.

179. Schmitz K, French SA, Jeffery RW. Correlates of changes in leisuretime physical activity over 2 years: the Healthy Worker Project. PrevMed. 1997;26:570–579.

180. Haynes R, Taylor D, Sackett D. Compliance in Health Care. Baltimore,Md: Johns Hopkins University Press; 1979.

181. Haynes RB, McDonald HP, Garg AX. Helping patients follow pre-scribed treatment: clinical applications. JAMA. 2002;288:2880–2883.

182. Rejeski WJ, Miller ME, King AC, Studenski SA, Katula JA, FieldingRA, Glynn NW, Walkup MP, Ashmore JA; LIFE Investigators. Pre-dictors of adherence to physical activity in the Lifestyle Interventionsand Independence for Elders pilot study (LIFE-P). Clin Interv Aging.2007;2:485–494.

183. Ziegelstein RC, Fauerbach JA, Stevens SS, Romanelli J, Richter DP,Bush DE. Patients with depression are less likely to follow recommen-dations to reduce cardiac risk during recovery from a myocardialinfarction. Arch Intern Med. 2000;160:1818–1823.

184. Ruscin JM, Semla TP. Assessment of medication management skills inolder outpatients. Ann Pharmacother. 1996;30:1083–1088.

185. Nikolaus T, Kruse W, Bach M, Specht-Leible N, Oster P, Schlierf G.Elderly patients’ problems with medication: an in-hospital andfollow-up study. Eur J Clin Pharmacol. 1996;49:255–259.

186. Donovan JL, Blake DR. Patient non-compliance: deviance or reasoneddecision-making? Soc Sci Med. 1992;34:507–513.

187. Burke LE, Dunbar-Jacob JM, Hill MN. Compliance with cardiovasculardisease prevention strategies: a review of the research. Ann Behav Med.1997;19:239–263.

188. Haynes RB, McDonald H, Garg AX, Montague P. Interventions forhelping patients to follow prescriptions for medications. CochraneDatabase Syst Rev. 2002:CD000011.

189. Kahn EB, Ramsey LT, Brownson RC, Heath GW, Howze EH, PowellKE, Stone EJ, Rajab MW, Corso P. The effectiveness of interventions toincrease physical activity: a systematic review. Am J Prev Med. 2002;22:73–107.

190. Trost SG, Owen N, Bauman AE, Sallis JF, Brown W. Correlates ofadults’ participation in physical activity: review and update. Med SciSports Exerc. 2002;34:1996–2001.

191. Eyler AA, Brownson RC, Donatelle RJ, King AC, Brown D, Sallis JF.Physical activity social support and middle- and older-aged minoritywomen: results from a US survey. Soc Sci Med. 1999;49:781–789.

192. Engbers LH, van Poppel MN, Chin A Paw M, van Mechelen W. Theeffects of a controlled worksite environmental intervention on deter-minants of dietary behavior and self-reported fruit, vegetable and fatintake. BMC Public Health. 2006;6:253.

193. Williamson DA, Anton SD, Han H, Champagne CM, Allen R, LeBlancE, Ryan DH, McManus K, Laranjo N, Carey VJ, Loria CM, Bray GA,Sacks FM. Adherence is a multi-dimensional construct in the POUNDSLOST trial. Obesity (Silver Spring). 2010;33:35–46.

194. Wadden TA, West DS, Neiberg RH, Wing RR, Ryan DH, Johnson KC,Foreyt JP, Hill JO, Trence DL, Vitolins MZ; Look AHEAD ResearchGroup. One-year weight losses in the Look AHEAD Study: Factorsassociated with success. Obesity (Silver Spring). 2009;17:713–722.

195. Sacks FM, Bray GA, Carey VJ, Smith SR, Ryan DH, Anton SD,McManus K, Champagne CM, Bishop LM, Laranjo N, Leboff MS,Rood JC, de Jonge L, Greenway FL, Loria CM, Obarzanek E, Wil-liamson DA. Comparison of weight-loss diets with different compo-sitions of fat, protein, and carbohydrates. N Engl J Med. 2009;360:859–873.

196. Pearson TA, McBride PE, Miller NH, Smith SC. 27th Bethesda Con-ference: matching the intensity of risk factor management with thehazard for coronary disease events. Task Force 8: Organization ofPreventive Cardiology Service. J Am Coll Cardiol. 1996;27:1039–1047.

197. Jordan TR, Dake JR, Price JH. Best practices for smoking cessation inpregnancy: do obstetricians/gynecologist use them in practice?J Womens Health. 2006;15:400–441.

198. Gordon NF, Salmon RD, Mitchell BS, Faircloth GC, Levinrad LI,Salmon S, Saxon WE, Reid KS. Innovative approaches to compre-hensive cardiovascular disease risk reduction in clinical andcommunity-based settings. Curr Atheroscler Rep. 2001;3:498–506.

199. Falk M. Compliance with treatment and the art of medicine. Am JCardiol. 2001;88:668–669.

200. Laschinger HK, McWilliam CL, Weston W. The effects of familynursing and family medicine clinical rotations on nursing and medicalstudents’ self-efficacy for health promotion counseling. J Nurs Educ.1999;38:347–356.

440 Circulation July 27, 2010

201. LaDuke S. Nurses’ perceptions: is your nurse uncomfortable or incom-petent? J Nurs Adm. 2000;30:163–165.

202. McDonald PE, Tilley BC, Havstad SL. Nurses’ perceptions: issues thatarise in caring for patients with diabetes. J Adv Nurs. 1999;30:425–430.

203. McBride PE, Plane MB, Underbakke G. Hypercholesterolemia: thecurrent educational needs of physicians. Am Heart J. 1992;123:817–824.

204. Orlandi MA. Promoting health and preventing disease in health caresettings: an analysis of barriers. Prev Med. 1987;16:119–130.

205. Walsh JM, McPhee SJ. A systems model of clinical preventive care: ananalysis of factors influencing patient and physician. Health Educ Q.1992;19:157–175.

206. Hill M, Miller N. Adherence to antihypertensive therapy. In: Izzo J,Black H, eds. Hypertension Primer. 3rd ed. Philadelphia, Pa: LippincottWilliams & Wilkins; 2003:390–393.

207. Redberg RF, Benjamin EJ, Bittner V, Braun LT, Goff DC Jr, Havas S,Labarthe DR, Limacher MC, Lloyd-Jones DM, Mora S, Pearson TA,Radford MJ, Smetana GW, Spertus JA, Swegler EW. AHA/ACCF 2009performance measures for primary prevention of cardiovascular diseasein adults: a report of the American College of Cardiology Foundation/American Heart Association task force on performance measures(writing committee to develop performance measures for primary pre-vention of cardiovascular disease) [published correction appears in Cir-culation. 2010;121:e445–e446]. Circulation. 2009;120:1296–1336.

208. Rutkow L, Vernick JS, Hodge JG Jr, Teret SP. Preemption and theobesity epidemic: state and local menu labeling laws and the nutritionlabeling and education act. J Law Med Ethics. 2008;36:772–789.

209. McColl K. New York’s road to health. BMJ. 2008;337:a673.210. Okie S. New York to trans fats: You’re out. N Engl J Med. 2007;356:

2017–2021.211. Diez-Roux AV, Nieto FJ, Caulfield L, Tyroler HA, Watson RL, Szklo

M. Neighborhood differences in diet: the Atherosclerosis Risk in Com-munities (ARIC) Study. J Epidemiol Community Health. 1999;53:55–63.

212. Wendel-Vos W, Droomers M, Kremers S, Brug J, van Lenthe F.Potential environmental determinants of physical activity in adults: asystematic review. Obes Rev. 2007;8:425–440.

213. Heath GW, Brownson RC, Kruger J, Miles R, Powell K, Ramsey L;Task Force on Community Preventive Services. The effectiveness ofurban design and land use and transport policies and practices toincrease physical activity: a systematic review. J Phys Act Health. 2006;3(suppl 1): S55–S76.

214. Diez-Roux AV, Nieto FJ, Muntaner C, Tyroler HA, Comstock GW,Shahar E, Cooper LS, Watson RL, Szklo M. Neighborhood envi-ronments and coronary heart disease: a multilevel analysis. Am JEpidemiol. 1997;146:48 – 63.

215. Dubowitz T, Heron M, Bird CE, Lurie N, Finch BK, Basurto-Davila R,Hale L, Escarce JJ. Neighborhood socioeconomic status and fruit andvegetable intake among whites, blacks, and Mexican Americans in theUnited States. Am J Clin Nutr. 2008;87:1883–1891.

216. Wechsler H, Basch CE, Zybert P, Lantigua R, Shea S. The availabilityof low-fat milk in an inner-city Latino community: implications fornutrition education. Am J Public Health. 1995;85:1690–1692.

217. Faskunger J, Poortvliet E, Nylund K, Rossen J. Effect of an environ-mental barrier to physical activity on commuter stair use. Scand J Nutr.2003;47:26–28.

218. Adams MA, Hovell MF, Irvin V, Sallis JF, Coleman KJ, Liles S.Promoting stair use by modeling: An experimental application of theBehavioral Ecological Model. Am J Health Promot. 2006;21:101–109.

219. US Department of Health and Human Services. Office of MinorityHealth: Minority populations. Available at: http://minorityhealth.hhs.gov/templates/browse.aspx?lvl�1&lvlID�7. Accessed November 1,2009.

220. Ogden CL, Carroll MD, Curtin LR, McDowell MA, Tabak CJ, FlegalKM. Prevalence of overweight and obesity in the United States,1999–2004. JAMA. 2006;295:1549–1555.

221. Cook NR, Cutler JA, Obarzanek E, Buring JE, Rexrode KM,Kumanyika SK, Appel LJ, Whelton PK. Long term effects of dietarysodium reduction on cardiovascular disease outcomes: observationalfollow-up of the trials of hypertension prevention (TOHP). BMJ. 2007;334:885–888.

222. Ornish D, Scherwitz LW, Billings JH, Brown SE, Gould KL, MerrittTA, Sparler S, Armstrong WT, Ports TA, Kirkeeide RL, Hogeboom C,Brand RJ. Intensive lifestyle changes for reversal of coronary heartdisease. JAMA. 1998;280:2001–2007.

223. Killingsworth R. Health promoting community design: a new paradigmto promote healthy and active communities. Am J Health Promot.2003;12:169–170.

224. Sallis JF, Cervero RB, Ascher W, Henderson KA, Kraft MK, Kerr J. Anecological approach to creating active living communities. Annu RevPublic Health. 2006;27:297–322.

225. Lloyd-Jones DM, Hong Y, Labarthe D, Mozaffarian D, Appel LJ, VanHorn L, Greenlund K, Daniels S, Nichol G, Tomaselli GF, Arnett DK,Fonarow GC, Ho PM, Lauer MS, Masoudi FA, Robertson RM, Roger V,Schwamm LH, Sorlie P, Yancy CW, Rosamond WD; American HeartAssociation Strategic Planning Task Force and Statistics Committee.Defining and setting national goals for cardiovascular health promotionand disease reduction: the American Heart Association’s StrategicImpact Goal through 2020 and beyond. Circulation. 2010;121:586–613.

226. ACC/AHA Task Force on Practice Guidelines. Methodology Manual forACC/AHA Guideline Writing Committees. American College of Car-diology Foundation and American Heart Association; 2006:1– 61.Available at: http://circ.ahajournals.org/manual/manual_I.shtml.Accessed June 21, 2010.

227. Keyserling TC, Ammerman AS, Davis CE, Mok MC, Garrett J, SimpsonR Jr. A randomized controlled trial of a physician-directed treatmentprogram for low-income patients with high blood cholesterol: theSoutheast Cholesterol Project. Arch Fam Med. 1997;6:135–145.

228. Diabetes Prevention Program. Diabetes Prevention Program: Study Doc-uments Web Site. Available at: http://www.bsc.gwu.edu/dpp/index.htmlvdoc. Accessed February 25, 2008.

KEY WORDS: AHA Scientific Statements � diet � lifestyle � activity,physical � skills, behavior change � reduction, cardiovascular risk �modification, lifestyle

Artinian et al Promoting Physical Activity and Dietary Changes 441