Effectiveness of interventions targeting physical activity, nutrition and healthy weight for university and college students: a systematic review and meta-analysis

This systematic review and meta-analysis examines the effectiveness of interventions aimed at improving physical activity, diet, and weight-related behaviors among university and college students. The review includes 41 studies and finds that interventions targeting physical activity and nutrition have significant positive effects, while weight loss outcomes are less successful. The study suggests that more research is needed to improve strategies for promoting healthy behaviors in tertiary education institutions.

REV I E W Open Access
Effectiveness of interventions targeting physica
activity,nutrition and healthy weight for
university and college students:a systematic
review and meta-analysis
Ronald C Plotnikoff1,2*
, Sarah A Costigan1,2
, Rebecca L Williams1,3
, Melinda J Hutchesson1,3
, Sarah G Kennedy1,2
,
Sara L Robards1,2
, Jennifer Allen2
, Clare E Collins1,3
, Robin Callister1,4
and John Germov5
Abstract
To examine the effectiveness of interventions aimed at improving physicalactivity,diet,and/or weight-related
behaviors amongst university/college students.Five online databases were searched (January 1970 to April2014).
Experimentalstudy designs were eligible for inclusion.Data extraction was performed by one reviewer using a
standardized form developed by the researchers and checked by a second reviewer.Data were described in a
narrative synthesis and meta-analyses were conducted when appropriate.Study quality was also established.
Forty-one studies were included;of these,34 reported significant improvements in one of the key outcomes.Of
the studies examining physicalactivity 18/29 yielded significant results,with meta-analysis demonstrating significant
increases in moderate physicalactivity in intervention groups compared to control.Of the studies examining
nutrition,12/24 reported significantly improved outcomes;only 4/12 assessing weightloss outcomes found
significantweightreduction.This appears to be the firstsystematic review of physical activity,diet and weight loss
interventions targeting university and college students.Tertiary institutions are appropriate settings for implementing
and evaluating lifestyle interventions,however more research is needed to improve such strategies.
Keywords: University,College,Tertiary education institutions,University students,Health promotion,Health behavior,
Healthy universities,Physical activity,Exercise,Diet,Nutrition,Weight loss
Introduction
Physical inactivity and poor dietary-intake are related be-
haviorsthat impacton health and wellbeing and the
maintenance of a healthy weight.These behaviors under-
pin risk of lifestyle related non-communicable conditions
[1].Risk for ischaemic heart disease,stroke,type two dia-
betes,osteoporosis,variouscancersand depression are
linked by behavioraland biomedicalhealth determinants
such asphysicalinactivity,poor dietary behaviorsand
overweight/obesity [2].
The health benefits of engaging in regular physicalac-
tivity are wellestablished foradults[3]. Strategiesto
promotephysicalactivityhavebecomean important
public health approach for the prevention of chronic dis-
eases [4]. The prevalence of achieving physical activity rec
ommendations declines rapidly between the ages of18
and 24 [5] when many young people are undertaking ter-
tiary education [6-8].For instance,in the United States
nearly half of all university students are not achieving rec-
ommended levels ofphysicalactivity [9].Australian data
in the ≥18 year age group indicate 66.9% are sedentary or
have low levels of physical activity during 2011-2012 [10].
Similarly in the United Kingdom,73% of male and 79% of
female university students do notmeetphysicalactivity
guidelines [6]. Further, Irwin [8] suggests that students liv-
ing on campus are less likely to be active, and thus may be
at greater risk of poor health.
* Correspondence:[e-mail]
1Priority Research Centre for PhysicalActivity and Nutrition,University of
Newcastle,Callaghan Campus,Newcastle,NSW,Australia
2Schoolof Education,Faculty of Education and Arts,University of Newcastle,
Callaghan Campus,Newcastle,NSW,Australia
Fulllist of author information is available at the end of the article
© 2015 Plotnikoff et al.;licensee BioMed Central.This is an Open Access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/4.0),which permits unrestricted use,distribution,and
reproduction in any medium,provided the originalwork is properly credited.The Creative Commons Public Domain
Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article,
unless otherwise stated.
Plotnikoff et al.InternationalJournalof BehavioralNutrition
and PhysicalActivity (2015) 12:45
DOI10.1186/s12966-015-0203-7

Dietary intake patterns that align with nationaldietary
guidelines are associated with reduced risk of developing
chronic conditions [11,12],however recent research sug-
geststertiary studentsdo not achieve these guidelines
[13-15].For instance,in the United States,university and
college students have sub-optimal dietary habits compared
to such recommendations [16].Similarly,Australian ter-
tiary studentsfail to consume the recommended daily
servings of fruit (50%) and vegetables (90%) [2]. While stu-
dents from the UK failto consume the recommended
daily intake of fruit and vegetables (88.7% and 83.5%,re-
spectively) [17].
Commencing college/university is often associated with
students having more autonomy over their dietary choices
(e.g.,food purchasing and preparation).Due to life stage,
students may not consider the risk of developing chronic
diseases when making food choices [18].Specifically,fac-
tors such as cost,skipping meals,inadequate variety of
foods,snacking,and frequent consumption offast foods
may increase students’risk of poor health [19].Indeed,
studies have reported that considerable weight gain occurs
during college/university [20,21].The associated food se-
lection skills and habits have long-term health impacts
[22].Further,within US institutions a great proportion of
freshmen (first year) live in college resident halls,which
provide commercially prepared food,take-away and pre-
prepared meals.This environment may further contribute
to subsequent poor food purchasing and preparation be-
haviors. Along with these dietary behaviors, physical activity
participation also declinesin university and college stu-
dents, which may be due to increased sedentary time when
studying and during examination periods [23].
Given the lack of physical activity and healthy eating it
is not surprising that the prevalence of overweight/obesity
has reached epidemic proportions in young adults.In the
USA, the age range of greatest increase in obesity (7.1% to
12.1%) is among young adults aged 18–29 years [7].In-
deed,late adolescence and early adulthood appear to be
significant periods oftransition,highlighting the import-
ance ofunderstanding factors such as attitudes towards
and knowledge ofhealth benefits,as these may be associ-
ated with physical activity levels, dietary behavior and obes-
ity prevalence [24].Improvements to lifestyle behaviors can
reduce or preventthe occurrence ofnon-communicable
diseases;therefore strategies to foster healthier lifestyles in
the working age population are essential.
Higher education institutions are an appropriate set-
ting to promote healthy lifestyles.First,universities and
colleges have the potentialto engage large numbers of
students in behavior change interventions,and the esti-
mated number of individuals participating in higher educa-
tion is continuing to rise [25].It is projected that student
numbers in American collegeswill reach 22 million in
2014,and that the number of students enrolled in higher
education worldwide willreach 262 million by 2025,a
marked increase from 178 million in 2010 [26].Second,
higher education institutions have access to a large propor
tion of students living away from home for the first time,
and have the capacity to provide supportand establish
healthy behavioralpatterns that may continue throughout
the lifespan.Third,universities and colleges are regarded
as organizationsthat follow high standardsof practice
which can establish research-based examplesfor sur-
rounding communities to follow.This allows for the op-
portunity and responsibility to develop and implement the
best available research evidence,and to set a benchmark
for other groups to follow [27].Universities and colleges
have a range of facilities, resources and qualified staff, com
monly including health professionals,idealfor implement-
ing initiatives to target lifestyle-related health issues. Finall
the possibility that exists for students to deliver initiatives
as a part oftheir study/training to become health profes-
sionals adds to the promise for tertiary education institu-
tions as ideal settings for promoting healthy lifestyles.
Evidencesuggeststhat intervention strategieshave
been successfulfor students in the highereducational
setting [1,5],particularly interventions that seek to em-
power individuals to achieve their fullpotentialthrough
creating learning and supportto improve health,well-
being and sustainability within the community [28].In
addition,whilstthe primary advantage ofimplementing
health promotion programs is to reduce individuals’ health
risks,the benefits to higher education institutions in attri-
tion,retention and academic performance are also poten-
tial gains [29].Although a recentreview examining the
effectivenessof interventionstargeting health behaviors
(physicalactivity,nutrition and healthy weight)amongst
university staff has been conducted [22],it appears that a
review investigating the effectiveness ofhealth behavior
interventions on these health behaviors/issues for univer-
sity students has not yet been performed.
Objective
The objective of this paper is to systematically review the
best available evidence regarding the impact of health be-
havior interventions to improve physical activity, diet and/
or weight outcomes and targeted at students enrolled in
tertiary education institutions.
Review
Methods
Data source
A structured electronic search employing PRISMA report-
ing guidelines [30] was performed on health-focused inter-
vention studies carried outin tertiary leveleducational
institutions and published between January 1970 and April
2014.MEDLINE with full text,PsychINFO,CINAHL,
ERIC and ProQuest were systematicallysearched
Plotnikoff et al.InternationalJournalof BehavioralNutrition and PhysicalActivity (2015) 12:45 Page 2 of 10

[22,31-34].The following search terms were used:(uni-
versity OR college) AND (health promotion OR interven-
tion OR program OR education)AND (behaviorOR
physicalactivity OR exercise OR dietOR nutrition OR
weight).Published articles in peer reviewed journals were
considered for the review. Bibliographies of selected studies
were also considered.Only manuscripts written in English
were considered for the review.Two reviewers independ-
ently assessed articles for study inclusion,initially based on
the title and abstract.Full texts were then retrieved and
assessed for inclusion.A third reviewer was used to make
the final decision in the case of discrepancies.
Study inclusion and exclusion criteria
Type of participants
Any study includingstudentsattendinginstitutions
within the tertiary education sector was included.If other
types ofparticipants,e.g.,staffwere also recruited,only
students’data were extracted.
Type of intervention (s)/phenomena of interest
Interventions deemed eligible for inclusion had to be im-
plemented within a tertiary education setting and have
the aim ofimproving physicalactivity and/or dietary in-
take and/or weight.Interventions ofall lengths were ac-
cepted for inclusion within the review.
Type of studies
All quantitative study designs (including randomized con-
trolled trials,non-randomized experimentaltrials,pre-
post with no control group) were eligible for inclusion.
Type of outcomes
This review considered the following outcome measures spe-
cific to the health behavior targeted (an increase in know-
ledge among participants was not a sufficient outcome):
i) Physical activity related outcomes:steps per day,
time spent undertaking vigorous and/or moderate
physical activity, VO2 max,muscular strength/
endurance,energy expenditure,flexibility;
ii) Nutrition outcomes:energy intake,macronutrient
composition,core food group consumption,diet
quality;and,
iii) Weight related outcomes:weight (kg or lbs),body
mass index (kg/m2) (BMI),waist circumference
(cm),% weight loss,% body fat,waist-to-hip ratio
(WHR).
Risk of bias
Risk ofbias was assessed for allincluded studies by two
independentreviewers (SK,SR) (a third reviewer[SC]
was consulted and consensus reached in the event ofa
disagreement)using the Academyof Nutrition and
Dietetics Quality Criteria Checklist: Primary Research tool
assessing 10 criteria [35].These criteria included whether:
(1) The study clearly stated the research question;(2) If
the selection of participants was free from bias;(3) If the
study groups were comparable;(4) Description of method
of handling withdrawals;(5) Use ofblinding;(6) Detailed
description ofinterventions and comparisons;(7) Clear
definition ofoutcomes and valid and reliable measure-
ments;(8) Appropriate statisticalanalysis;(9) Consider-
ation oflimitations;and,(10)Likelihood ofbias due to
funding.Study quality was classed as positive if criteria 2,
3, 6 and 7,as wellas one other validity criteria question
were scored with a ‘yes’,neutralif criteria points 2,3 6
and 7 did not score a ‘yes’,or negative if more than six of
the validity criteria questions were answered with a ‘no’.
Data extraction
Data extraction was performed by two reviewers (SK,SR)
using a standardized form developed by the researchers.
The data extraction consisted of11 dimensions;country
of origin,target sample and size,participants’mean age,
duration of study,intervention description,participant re-
tention,health behavior,study design,outcomes,results,
and significance of results (see Additional file 1:Table S1,
Additionalfile 2:Table S2,and Table 1).Extraction was
checked foraccuracy and consistency by a third re-
viewer (SC).
Meta-analysis
Results were pooled in meta-analysis ifthey were avail-
able as finalvalues atpost-intervention,the number of
participants was recorded and interventions were suffi-
cientlysimilarfor comparison.If standard deviations
were notavailable,but other statistics (e.g.,95% CIor
standard errors) were available,they were converted ac-
cording to thecalculationsoutlined in theCochrane
Handbook for Systematic Reviews ofInterventions [36].
Heterogeneity was assessed using chi-squared with sig-
nificant heterogeneity assigned at a P value < 0.10.If sig-
nificant heterogeneity existed,the random effects model
was used for statistical analysis;if homogenous,the fixed
effect modelwas used.The data from individualstudies
on physicalactivity were combined across studies using
standardized mean difference (SMD)due to the differ-
ences in reported metrics for total, moderate and vigorous
physicalactivity.A unit conversion was not undertaken.
Therefore,the meta-analyticalresults do notreflectthe
specific magnitude of effects for each study, but rather the
extent to which they are more successful against controls.
When a study compared multiple treatment groups with a
single control,the sample size of the controlwas divided
equally across the treatmentgroup arms so the partici-
pants were not counted more than once in the analysis.
All meta-analyses were conducted using Review Manager
Plotnikoff et al.InternationalJournalof BehavioralNutrition and PhysicalActivity (2015) 12:45 Page 3 of 10

Table 1 Critical appraisal criteria of study methodologies
Study Criteria
1
Criteria
2
Criteria
3
Criteria
4
Criteria
5
Criteria
6
Criteria
7
Criteria
8
Criteria
9
Criteria
10
Classification
1.Abu-Moghliet al.2010 [1] 1 0 0 0 0 0 1 1 1 1 ∅
2.AfifiSoweid et al.2003 [69] 1 0 0 0 0 1 0 0 1 1 −
3.Alpar et al.2008 [67] 1 0 0 1 0 1 1 1 0 1 ∅
4.Bowden et al.2007 [37] 1 1 0 0 0 1 0 1 1 1 ∅
5.Boyle et al.2011 [38] 1 0 1 0 0 1 0 1 1 1 ∅
6.Brown et al.2011 [39] 1 0 0 0 0 1 1 1 1 1 ∅
7.Buscemiet al.2011 [40] 1 1 1 0 0 1 0 1 1 1 ∅
8.Cardinalet al.2002 [41] 1 0 0 0 0 1 1 1 1 1 ∅
9.Cavallo et al.2012 [19] 1 0 1 0 0 1 1 1 1 1 ∅
10.Chen et al.1989 [42] 1 0 0 0 0 1 0 0 0 1 −
11.Claxton et al.2009 [43] 1 0 0 1 0 0 1 1 0 1 ∅
12.Evans & Mary 2002 [43] 1 0 0 0 0 1 0 1 0 1 −
13.Fischer & Bryant 2008 [45] 1 1 1 0 0 0 1 1 1 1 ∅
14.Gieck & Olsen 2007 [46] 1 1 0 0 0 1 1 1 1 1 ∅
15.Gow et al.2010 [47] 0 1 1 1 0 1 1 1 1 1 +
16.Gray et al.1987 [47] 0 1 0 0 0 0 0 0 1 1 −
17.Grim et al.2011 [5] 1 0 0 1 0 1 1 1 1 1 ∅
18.Ha & Caine-Bish 2009 [49] 1 0 0 0 0 1 1 1 1 1 ∅
19.Hager et al.2012 [50] 1 1 0 0 0 1 1 1 1 1 ∅
20.Harvey-Berino et al.2012 [52] 1 0 0 0 0 1 0 0 1 1 −
21.Hekler et al.2010 [51] 1 0 0 0 0 1 1 1 1 1 ∅
22.Huang et al.2009 [7] 1 1 1 0 0 1 1 1 1 1 +
23.Ince 2008 [68] 1 1 0 0 0 1 0 1 0 1 ∅
24.Kolodinsky et al.2008 [53] 1 1 0 0 0 0 0 0 1 1 −
25.Lachausse 2012 [54] 1 1 0 0 0 1 1 1 1 1 ∅
26.LeCheminant et al.2011 [55] 1 1 0 0 0 1 1 1 1 1 ∅
27.Magoc et al.2011 [57] 1 1 1 0 0 1 1 1 1 1 +
28.Martens et al.2012 [40] 1 1 1 0 1 1 0 1 1 1 ∅
29.McClary King et al.2013 [56] 1 0 0 0 0 1 1 1 1 1 ∅
30.Musgrave & Thornbury 1976 [59]0 1 0 0 0 1 0 0 0 1 −
31.Pearce & Cross 2013 [31] 1 0 0 0 0 1 1 1 1 1 ∅
32.Pearman et al.1997 [60] 0 1 0 0 0 0 0 1 1 1 −
33.Peterson et al.2010 [61] 1 1 0 0 0 1 0 1 1 1 ∅
34.Reed et al.2011 [62] 1 1 0 0 1 1 0 1 1 1 ∅
35.Sallis et al.1999 [63] 1 1 0 0 0 1 1 1 1 1 ∅
36.Skar et al.2011 [70] 1 1 1 1 1 1 0 1 0 1 ∅
37.Tully & Cupples 2011 [71] 1 1 0 0 1 1 0 1 1 1 ∅
38.Wadsworth et al.[64] 1 1 0 0 0 1 1 1 0 1 ∅
39.Werch et al.2007 [65] 1 1 1 1 0 1 1 1 1 1 +
Plotnikoff et al.InternationalJournalof BehavioralNutrition and PhysicalActivity (2015) 12:45 Page 4 of 10

5.2;the results were calculated by weighting the amount
of information they contribute i.e.,the inverse variances
of their effect estimates.Intention-to-treat analyses were
used where available/reported in the studies.If this infor-
mation was not available completers analyses was used.
Results
Overall,41 studiestargeting improvementsin student
health outcomes (physical activity, diet, weight loss) within
tertiary education settings met the inclusion/exclusion cri-
teria. Study characteristics (i.e., country, target sample and
size,age,duration,intervention and retention) and risk of
bias scores are summarised in Additional file 1:Table S1.
Risk of bias assessment indicated eight studies had a negative
rating (high risk ofbias),30 were considered neutral,and
the remaining four had a positive rating (low risk of bias).
Of the 41 studies identified,33 were conducted in the
United States[5,19,37-66],two in Turkey [67,68]and
one each in Jordan [1],Lebanon [69],Scotland [70],
Ireland [71], Taiwan [72] and Australia [9].Study designs
includedrandomizedcontrolledtrials (n = 16),non-
randomized controlled trials(n = 12)and pre-postde-
signswith no controlgroup (n = 13).Study durations
ranged from a 30-minute one-on-one briefmotivational
intervention [58]to an intervention spanning four aca-
demiccalendaryears[67].Weight loss was the sole
focus in two studies [52,59],physicalactivity in 11 stud-
ies [5,19,41,43,45,46,57,58,63,70,72],and nutrition was
the focus of10 studies [9,39,42,44,48,49,51,53,61,62].A
combination ofweightloss and/or physicalactivity
and/or nutrition outcomes were examined by 18 studies
[1,37,38,40,47,50,54-56,60,64-69,71,73].Studyparticipant
numbers ranged from 16 [53] to 2971 [50]. Retention rates
ranged from 36.6% [46] to 100% [49,51,53,62,71]; five stud-
ies [19,42,44,66,68] did not report retention rates.
Three studiesdid not reportthe sex distribution of
participants[41,57,68].Of the remaining studies,four
had even sex distribution [48,56,62,69],three had a
majorityof male participants[43,55,61];23 studies
were comprised of majority female participants
[1,5,9,37-40,42,44,47,49,50,52-54,58-60,63,65,70,71,73];
and eightstudiesconsisted ofentirely female samples
[19,45,46,51,64,66,67,72].In general,demographic charac-
teristics of participants such as age were not consistently
reported.
Effectiveness of interventions
Physical activity and fitness outcomes
As represented in Additionalfile 2:Table S2,of the 41
studies in our review,29 examined physicalactivity (11
exclusively,18 in combination with other health behav-
iors).Of these 29 studies,the average risk ofbias classi-
fication was neutral.Of the studies investigating change
in physicalactivity or fitness behavior,18 of 29 reported
significant improvements from pre- to post-intervention.
In five studies a significant increase in physical activity mi-
nuteswas achieved [50,57,63,70,71];in five studiesthe
number of days participating in physical activity increased
[5,43,58,64,65]; exercise duration increased in three studie
[38,65,67];Metabolic Equivalent of Task (METs) increased
in three studies [60,68,72];exercise barriers decreased in
one study [56];and PhysicalActivity Readiness Question-
naire (PAR-Q) scores improved in one study [50].
Meta-analysis
Total physical activity
Five studies comparing interventions targeting health be-
haviors to a control condition that assessed total physical
activitylevel at post-intervention werecombined in
meta-analysis(see Figure 1).Three of the studiesin-
cluded multiple intervention arms compared to a single
controlgroup,therefore 10,intervention versus control
comparisons were included in the analysis.
The studies were significantly heterogeneous (χ2 = 25.65,
d.f.= 9 [P = 0.002],I 2 = 65%) and demonstrated no signifi-
cant difference in total physical activity between interven-
tion and controlgroups at post-intervention (SMD −0.11
[−0.30,0.08], Z = 1.13 P = 0.26).
Table 1 Critical appraisal criteria of study methodologies (Continued)
40.Werch et al.2008 [73] 1 1 0 1 0 1 1 1 1 1 ∅
41.Yakusheva et al.2011 [66] 1 1 0 0 0 0 0 1 1 1 ∅
37 25 10 7 4 34 23 35 33 41
Criteria:1) Was the research question clearly stated? 2) Was the selection of study subjects/patients free from bias? 3) Were study groups comparable? 4) W
method of handling withdrawals described? 5) Was blinding used to prevent introduction of bias? 6) Were intervention/therapeutic regimens/exposure fac
procedure and any comparison(s) described in detail? Were intervening factors described? 7) Were outcomes clearly defined and the measurements valid
reliable? 8) Was the statisticalanalysis appropriate for the study design and type of outcome indicators? 9) Were conclusions supported by results with biases a
limitations taken into consideration? 10) Is bias due to study’s funding or sponsorship unlikely?#
1 = Yes;0 = No;0 = Unclear.
MINUS/NEGATIVE (−) If most (six or more) of the answers to the above validity questions are “No”,the report should be designated with a minus (−) symbol on
the Evidence Worksheet.
NEUTRAL (∅) If the answers to validity criteria questions 2,3,6,and 7 do not indicate that the study is exceptionally strong,the report should be designated with
a neutral (∅) symbol on the Evidence Worksheet.
PLUS/POSITIVE (+) If most of the answers to the above validity questions are “Yes” (including criteria 2,3,6,7 and at least one additional“Yes”),the report should
be designated with a plus symbol (+) on the Evidence Worksheet.
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Vigorous physical activity
Five studies comparing interventions targeting health be-
haviors to a control condition that assessed vigorous phys-
ical activity levels at post-intervention were combined in a
meta-analysis (see Figure 1).Two of the studies included
multiple intervention arms compared to a single control
group;therefore eight,intervention versus controlcom-
parisons were included in the analysis.
The studieswere significantlyheterogeneous(χ2 =
44.86,d.f.= 7 [P < 0.001],I 2 = 84%) and demonstrated no
Figure 1 Meta-analysis of total (panel 1),vigorous (panel 2) and moderate (panel 3) physical activity.
Plotnikoff et al.InternationalJournalof BehavioralNutrition and PhysicalActivity (2015) 12:45 Page 6 of 10

significantdifference in vigorous physicalactivity levels
between the intervention and controlgroupsat post-
intervention (SMD 0.28 [−0.08,0.63],Z = 1.54 P = 0.12)
(see Figure 1).
Moderate physical activity
As represented in Figure 1,five studies comparing inter-
ventions targeting health behaviors to a controlcondi-
tion that assessed moderate physicalactivity levelsat
post-intervention were combined in meta-analysis.Two
of the studies included multiple intervention arms com-
pared to a single controlgroup;therefore eight,inter-
vention versus control comparisons were included in the
analysis.
The studies were homogenous (χ2 = 6.86,d.f. = 7 [P =
0.44], I2 = 0%) and demonstrated significantly greater mod-
erate physical activity levels in the intervention group com-
pared to the control group at post intervention (SMD 0.18
[0.06,0.30], Z = 2.84 P = 0.005).
Nutrition outcomes
Of the 41 included studies,24 reported nutrition out-
comes (10 examined nutrition exclusively),with fruit and
vegetable intake the most reported outcome, used in 12 of
the reported studies [39,40,44,47,49-51,54,56,62,65,73].Of
the 24 studies,the average risk of bias rating was neutral.
Six studies had a negative rating,sixteen were neutral and
two had a positive rating.
Interventions were found to be effective in improving nu-
trition behaviors in 12 of the 24 studies [1,39,44,49-51,54,
60-62,65,68]. In three studies a significant improvement in
dietquality was achieved [1,61,68];six studies reported
vegetable intake increases [39,44,49-51,54];in six studies
fruit intake increased [39,44,49,50,54,62];fat intake was
reduced in four studies [44,51,60,61];fewer calories were
consumed in one study [60];frequency ofwholegrain
product consumption was increased in one study [50];and
consumption ofhealthy fats increased in one study [65].
Due to the heterogeneity and lack of standard methods to
assess dietary intake within the nutrition domain,a meta-
analysis was unable to be conducted.
Weight outcomes
Of the 41 included studies, 12 reported weight-related out-
comes (two examined weight exclusively) [37,38,40,47,50,
52,54,55,59,64,66,71] and of these 12,four reported signifi-
cantimprovements in these outcomes [38,47,52,66].The
average risk of bias rating for the 12 studies was neutral. A
significant reduction in waist-to-hip ratio was reported in
one study [38];in one study BMI decreased significantly
[47];one study reported significant weight loss [52];and a
significant increase in the number of participants trying to
lose weightwas reported by one study [66].Due to the
variation in aimsand measureswithin the domain of
weight, a meta-analysis was not conducted.
Discussion
The current review identified 41 studies that investigated
the impactof lifestyle interventions targeting improve-
mentof health outcomes (specifically physicalactivity,
diet or weight)for students within the tertiary sector.
Most studies reported atleastone significantimprove-
mentin a health outcome variable,with a numberof
studies having multiple significant impacts.Study results
were mostly positive,with at leasthalf of the studies
for physicalactivity and nutrition reporting significant
outcomes.These included18/29 studiesexamining
physicalactivity thatfound significanteffectsinclud-
ing increased physicalactivity minutes,an increase in
the number of days participating in physical activity and
also in exercise duration,increased METsand PAR-Q
scores and a decrease in barriers to exercise.In addition,
results ofthe meta-analysis suggestthe studies target-
ing moderatephysicalactivitydemonstrated signifi-
cantly greatermoderate physicalactivity levels in the
intervention group compared to the controlgroup at
postintervention.Of the studies examining nutrition,
50% reported significantimprovements,including im-
proved diet quality,increased fruit,vegetable and whole-
grain intake,and healthy fats and a reduction in overall
fat intake and calories.Of the studies examining body
weight,four of 12 resulted in significantoutcomes in-
cluding reductions in weight,BMI, and WHR and/or
an increasein the numberof participantstrying to
lose weight.
Interventionsspanning a university semesteror less
(≤12 weeks)generally resulted in a greater number of
significantoutcomesin comparison to interventions
with a duration of more than a semester.In addition,in-
terventions targeting nutrition only resulted in more sig-
nificant outcomes in comparison to targeting PA,weight
or multiple behaviours. For instance, of the ten intervention
targeting dietary behaviour,eight (80%) had significant re-
sults and the majority of these studies (7/8) were ≤12 week
For PA only studies,seven ofthe 11 (64%) interventions
had significant results,and of these seven studies five had
a duration of≤12 weeks.Of the two studies examining
weightonly interventions,only the 12 week study re-
ported significant results.Furthermore,when targeting a
combination ofbehaviours,11 of18 (61%) interventions
had significant results, and just over half of these interven-
tions had a duration of ≤12 weeks (6/11).
Less than half of the studies in each category were ran-
domized controlled trials,however there was no trend
(based on study counts)towards study design influen-
cing the effectiveness of interventions.The vast majority
of the studies were conducted in the USA (n = 31)and
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therefore the global generalizability of these results must
be interpreted with caution.
With few exceptions,participantnumberswere sur-
prisingly smallgiven the large institutions from which
participants were drawn.Additionally,participants were
overwhelmingly female,which may be due in part to the
higher percentage of females enrolled in some universities
and colleges.This raises questions about the approaches
used to recruit participants or the intrinsic appeal of the in-
terventionstrialed.Indeed,resultsfrom a questionnaire
examining gender differences in the health habits of univer-
sity students showed that males were less interested in nu-
trition advice and health-enhancing behaviors,suggesting
that interventions targeting health behaviors in university/
college students may need to be gender-specific to address
the different needs and interests of both sexes [15].
The transition from secondary to tertiary education
often results in an increase in health risk secondary to a
decrease in physical activity and increase in poor dietary
choices [74].For many students,making the transition
to tertiary education coincides with more freedom and
controlover their lives.However,this can contribute to
the increases in risk taking behaviors that are evident in
this population [75].With this new-found independence,
many students may not have developed skills such as self-
efficacy and accountability,leaving them at higher risk of
adopting unhealthy behaviors.A number of studies in this
review successfully targeted self-efficacy [5,7,39,46,54,57,64]
to improve health behaviors.
Interventionsthatwere embedded within university/
college courses were effective at improving physicalac-
tivity,nutrition and weight-related outcomes.Course-
embedded interventionsinvolvefrequentface-to-face
contactwith facilitators.It has been suggested thatfre-
quent professionalcontact may improve health outcomes
by enhancing vigilance and providing encouragement and
support[76].Additionally,interventions where students
received feedback on their progress appeared to be more
effective than simply attending lectures or receiving edu-
cational resources.
Universities and colleges are an idealsetting for imple-
mentation of health promotion programs as they support
a large studentpopulation atkey time for the develop-
ment of lifestyle skills and behaviors.Students have access
to world-class facilities,technology,and highly educated
staff including a variety of health disciplines,all of which
could contribute to the developmentof highly effective
health promoting interventions.A number ofstudies in
this review utilized university facilities, such as fitness cen-
tresand designated walking tracks,showing significant
improvements in physicalactivity outcomes.Besides ease
of access for students,use ofexisting facilities and re-
sources is also cost-effective, which is often a major limita-
tion of health promotion programs.
Conclusions
This study extends the current literature examining the
effectiveness ofinterventions targeting physicalactivity,
nutrition and weight-loss behaviors amongstuniversity
and college students.To the best ofthe authors’know-
ledge itis the firstsystematic review examining health
behaviors of students within a tertiary education setting.
Some limitations ofthe field existwhich should be ac-
knowledged.First,the majority of studies examined were
conducted in the USA,which may limit interpretations
and globalgeneralizability ofresults.Second,only four
of the 41 studies that met the inclusion criteria showed
a positive result in meeting the risk ofbias validity cri-
teria questions.Also, the potentialeffectof publication
bias mustbe considered,as the observationsmade in
this review did notinclude grey literature (e.g.,unpub-
lished dissertations).
This review has severalstrengths.It employed a com-
prehensive search strategy,adhered to the PRISMA proto-
col with two reviewersused forthe identification and
evaluation of studies [30],assessed study risk ofbias with
two independent reviewers using the Academy of Nutrition
and Dietetics Quality Criteria Checklist,and included a
meta-analyses for physical activity.
Tertiary education students within the university/college
setting are ideal targets for lifestyle interventions aimed at
improving health behaviors.Within this setting,students
are often surrounded by an abundance of research expert-
ise, multi-disciplinaryhealth professionals,and world-
class facilities and resources making this potentially an
ideal health-promoting environment.Additionally,stu-
dents are in a learning environment and are still at an age
where health behaviors that impact on health later in life
can be improved.Therefore,there is significant scope for
implementation oflifestyle interventions to improve the
health of this group that represents a significant propor-
tion of our population.
Additional files
Additional file 1: Table S1. Study Characteristics.
Additional file 2: Table S2. Study Results.
Competing interests
The authors declare that they have no competing interests.
Authors’contributions
RCP,SAC,CEC,RC and JG conceptualized and designed the study.SAC and
JA drafted the introduction section.SAC,RLW,SGK,SLR extracted the data.
MJH conducted the statisticalanalyses.Allauthors contributed to the writing
and editing of the manuscript.Allauthors read and approved the final
manuscript.
Acknowledgements
RCP is supported by a National Health & Medical Research Council (NH & MR
Senior Research Fellowship.
Plotnikoff et al.InternationalJournalof BehavioralNutrition and PhysicalActivity (2015) 12:45 Page 8 of 10

Author details
1Priority Research Centre for PhysicalActivity and Nutrition,University of
Newcastle,Callaghan Campus,Newcastle,NSW,Australia.2Schoolof
Education,Faculty of Education and Arts,University of Newcastle,Callaghan
Campus,Newcastle,NSW,Australia.3Schoolof Health Sciences,Faculty of
Health,University of Newcastle,Callaghan Campus,Newcastle,NSW,
Australia.4Schoolof BiomedicalSciences and Pharmacy,Faculty of Health,
University of Newcastle,Callaghan Campus,Newcastle,NSW,Australia.
5Schoolof Humanities and SocialScience,Faculty of Education and Arts,
University of Newcastle,Callaghan Campus,Newcastle,NSW,Australia.
Received:11 August 2014 Accepted:10 March 2015
References
1. Abu-MoghliFA,Khalaf IA,BarghotiFF,Abu-MoghliFA,Khalaf IA,Barghoti
FF.The influence of a health education programme on healthy lifestyles
and practices among university students.Int J Nurs Pract.2010;16:35–42.
2. Australian Institute of Health and Welfare.Risk factors contributing to
chronic disease.In:Book Risk factors contributing to chronic disease.
Canberra:AIHW;2012.
3. ReinerM, Niermann C,Jekauc D,WollA. Long-term health benefits of
physicalactivity–a systematic review oflongitudinalstudies.BMC Public
Health.2013;13:813.
4. BonevskiB,Guillaumier A,PaulC,Walsh R.The vocationaleducation setting
for health promotion:a survey of students’health risk behaviours and
preferences for help.Health Promot J Austr.2014;24:185–91.
5. Grim M,Hortz B,Petosa R,Grim M,Hortz B,Petosa R.Impact evaluation of a
pilot web-based intervention to increase physical activity.Am J Health Promot.
2011;25:227–30.
6. Haase A,Steptoe A,Sallis JF,Wardle J.Leisure-time physicalactivity in
university students from 23 countries:associations with health beliefs,risk
awareness,and nationaleconomic development.Prev Med.2004;39:182–90.
7. Huang TT-K,Harris KJ,Lee RE,Nazir N,Born W,Kaur H.Assessing overweight,
obesity,diet,and physicalactivity in college students.J Am CollHealth.
2003;52:83–6.
8. Irwin JD.Prevalence of university students’sufficient physicalactivity:
a systematic review.Percept Mot Skills.2004;98:927–43.
9. Weinstock J.A review of exercise as intervention for sedentary hazardous
drinking college students:rationale and issues.J Am CollHealth.
2010;58:539–44.
10. Australian Bureau of Statistics.Australian Health Survey:First Results.In:
Book Australian Health Survey:First Results.Canberra:ABS;2012.
11. Wirt A,Collins CE.Diet quality–what is it and does it matter? Public Health
Nutr.2009;12:2473–92.
12. NationalHealth and MedicalResearch Council.Australian Dietary Guidelines.
In:Book Australian Dietary Guidelines.Canberra:NHMRC;2013.
13. Davy SR,Benes BA,DriskellJA. Sex differences in dieting trends,eating
habits,and nutrition beliefs of a group of midwestern college students.
J Am Diet Assoc.2006;106:1673–7.
14. Haberman S,Luffey D.Weighing in college students’diet and exercise
behaviors.J Am CollHealth.1998;46:189–91.
15. Von Bothmer MI,Fridlund B.Gender differences in health habits and in
motivation for a healthy lifestyle among Swedish university students.Nurs
Health Sci.2005;7:107–18.
16. McKinney CE.Assessment of dietary behaviors of college students
participating in the health promotion program BUCS:live well.2013.
17. ElAnsariW,Stock C,John J,Deeny P,Phillips C,Snelgrove S,et al.Health
promoting behaviours and lifestyle characteristics of students at seven
universities in the UK.Cent Eur J Public Health.2011;19:197.
18. Kattelmann KK,White AA,Greene GW,Byrd-Bredbenner C,Hoerr SL,Horacek
TM,et al.Development of Young Adults Eating and Active for Health (YEAH)
internet-based intervention via a community-based participatory research
model.J Nutr Educ Behav.2014;46:S10–25.
19. Cavallo DN,Tate DF,Ries AV,Brown JD,DeVellis RF,Ammerman AS.A social
media–based physicalactivity intervention:a randomized controlled trial.
Am J Prev Med.2012;43:527–32.
20. Gropper SS,Simmons KP,ConnellLJ,Ulrich PV.Changes in body weight,
composition,and shape:a 4-year study of college students.ApplPhysiol
Nutr Metab.2012;37:1118–23.
21. Fedewa MV,Das BM,Evans EM,Dishman RK.Change in weight and
adiposity in college students:a systematic review and meta-analysis.Am J
Prev Med.2014;47:641–52.
22. SmallM,Bailey-Davis L,Morgan N,Maggs J.Changes in eating and physical
activity behaviors across seven semesters of college living on or off campus
matters.Health Educ Behav.2012;134:885–91.
23. Buckworth J,Nigg C.Physicalactivity,exercise,and sedentary behavior in
college students.J Am CollHealth.2004;53:28–34.
24. Nelson MC,Kocos R,Lytle LA,Perry CL.Understanding the perceived
determinants of weight-related behaviors in late adolescence:a qualitative
analysis among college youth.J Nutr Educ Behav.2009;41:287–92.
25. United Nations EducationalScientific and CulturalOrganization.Trends in
GlobalHigher Education:Tracking an Academic Revolution.In:Book Trends
in GlobalHigher Education:Tracking an Academic Revolution.Paris:
UNESCO;2009.
26. Davis DV,Mackintosh B.Making a Difference:Australian International
Education.Sydney:New South Publishing;2012.
27. Fredman P.Universities as role models for sustainable development.In
European University Association AnnualConference:The Sustainability of
European Universities.Warwick;2012.
28. Knight A,La Placa V.Healthy universities:taking the university of Greenwich
healthy universities initiative forward.Int J Health Promot Educ.2013;51:41–9.
29. Zins JE.Building academic success on socialand emotionallearning:What
does the research say?:Teachers College Press.2004.
30. LiberatiA,Altman DG,Tetzlaff J,Mulrow C,Gøtzsche PC,Ioannidis JPA,et al.
The PRISMA statement for reporting systematic reviews and meta-analyses
of studies that evaluate health care interventions:explanation and elaboration.
PLoS Med.2009;6:e1000100.
31. Livhits M,Mercado C,Yermilov I,Parikh JA,Dutson E,Mehran A,et al.Is
socialsupport associated with greater weight loss after bariatric surgery?:
a systematic review.Obes Rev.2011;12:142–8.
32. Sanders L,Huang J,Krumholz HM,Olkin I,Gardner CD,Bravata DM.Efficacy
and safety of Low-carbohydrate diets:a systematic review.J Am Med Assoc.
2003;289:1837–50.
33. Franz MJ,VanWormer JJ,Crain AL,Boucher JL,Histon T,Caplan W,et al.
Weight-loss outcomes:a systematic review and meta-analysis of weight-loss
clinicaltrials with a minimum 1-year follow-up.J Am Diet Assoc.
2007;107:1755–67.
34. Weinheimer EM,Sands LP,CampbellWW.A systematic review of the
separate and combined effects of energy restriction and exercise on fat-free
mass in middle-aged and older adults:implications for sarcopenic obesity.
Nutr Rev.2010;68:375–88.
35. Evidence Analysis Manual:Steps in the Academy Evidence Analysis Process.
[http://www.adaevidencelibrary.com/files/Docs/2012_Jan_EA_Manual.pdf]
36. Higgins JP,Green S.Cochrane handbook for systematic reviews of
interventions:Version 4.2.5.The Cochrane Library:Wiley Blackwell;2005.
37. Bowden RG,Lanning BA,Doyle EI,Slonaker B,Johnston HM,Scanes G,et al.
Systemic glucose levelchanges with a carbohydrate-restricted and higher
protein diet combined with exercise.J Am CollHealth.2007;56:147–52.
38. Boyle J,Mattern CO,Lassiter JW,Ritzler JA,Boyle J,Mattern CO,et al.
Peer 2 peer:efficacy of a course-based peer education intervention to
increase physicalactivity among college students.J Am CollHealth.
2011;59:519–29.
39. Brown KN,Wengreen HJ,Vitale TS,Anderson JB,Brown KN,Wengreen HJ,
et al.Increased self-efficacy for vegetable preparation following an online,
skill-based intervention and in-class tasting experience as a partof
a generaleducation college nutrition course.Am J Health Promot.
2011;26:14–20.
40. BuscemiJ, Yurasek AM,Dennhardt AA,Martens MP,Murphy JG.A
randomized trialof a brief intervention for obesity in college students.Clin
Obes.2011;1:131–40.
41. CardinalBJ,Jacques KM,Levy SS.Evaluation of a university course aimed at
promoting exercise behavior.J Sports Med Phys Fitness.2002;42:113–9.
42. Chen Jr MS,Minton JP,Adams B.Changing college students’lifestyles in
favor of cancer prevention:a case study.J Cancer Educ.1989;4:49–54.
43. Claxton D,Wells GM,Claxton D,Wells GM.The effect of physicalactivity
homework on physicalactivity among college students.J Phys Act Health.
2009;6:203–10.
44. Evans AE,Mary KS,Evans AE,Mary KS-M.The rightbite program:
a theory-based nutrition intervention ata minority college campus.
J Am DietAssoc.2002;102:S89–93.
Plotnikoff et al.InternationalJournalof BehavioralNutrition and PhysicalActivity (2015) 12:45 Page 9 of 10

45. Fischer DV,Bryant J,Fischer DV,Bryant J.Effect of certified personaltrainer
services on stage of exercise behavior and exercise mediators in female
college students.J Am CollHealth.2008;56:369–76.
46. Gieck DJ,Olsen S,Gieck DJ,Olsen S.Holistic wellness as a means to
developing a lifestyle approach to health behavior among college students.
J Am CollHealth.2007;56:29–35.
47. Gow RW,Trace SE,Mazzeo SE,Gow RW,Trace SE,Mazzeo SE.Preventing
weight gain in first year college students:an online intervention to prevent
the “freshman fifteen”.Eat.2010;11:33–9.
48. Gray CH,Colome JS,Curry-Daly JR.Elective cancer education:how effective
from the public health viewpoint? Am J Public Health.1987;77:1207–9.
49. Ha EJ,Caine-Bish N,Ha E-J,Caine-Bish N.Effect of nutrition intervention
using a generalnutrition course forpromoting fruitand vegetable
consumption among college students.J Nutr Educ Behav.2009;41:103–9.
50. Hager R,George JD,LeCheminant JD,Bailey BW,Vincent WJ,Hager R,et al.
Evaluation of a university generaleducation health and wellness course
delivered by lecture or online.Am J Health Promot.2012;26:263–9.
51. Hekler EB,Gardner CD,Robinson TN,Hekler EB,Gardner CD,Robinson TN.
Effects of a college course about food and society on students’eating
behaviors.Am J Prev Med.2010;38:543–7.
52. Harvey-Berino J,Pope L,Gold BC,Leonard H,Belliveau C,Harvey-Berino J,
et al.Undergrad and overweight:an online behavioralweight management
program for college students.J Nutr Educ Behav.2012;44:604–8.
53. Kolodinsky J,Green J,Michahelles M,Harvey-Berino JR,Kolodinsky J,Green J,
et al.The use of nutritional labels by college students in a food-court setting.
J Am Coll Health.2008;57:297–302.
54. Lachausse RG,Lachausse RG.My student body:effects of an internet-based
prevention program to decrease obesity among college students.J Am Coll
Health.2012;60:324–30.
55. LeCheminant JD,Smith JD,Covington NK,Hardin-Renschen T,Heden T,
LeCheminant JD,et al.Pedometer use in university freshmen:a randomized
controlled pilot study.Am J Health Behav.2011;35:777–84.
56. McClary King K,Ling J,Ridner SL,Jacks DE,Newton KS,Topp RV.Fit Into
College II:physicalactivity and nutrition behavior effectiveness and
programming recommendations.Recreation Sports J.2013;37:29–41.
57. Magoc D,Tomaka J,Bridges-Arzaga A,Magoc D,Tomaka J,Bridges-Arzaga
A.Using the web to increase physicalactivity in college students.Am J
Health Behav.2011;35:142–54.
58. Martens MP,BuscemiJ, Smith AE,Murphy JG,Martens MP,BuscemiJ, et al.
The short-term efficacy ofa briefmotivationalintervention designed to
increase physicalactivity among college students.J Phys ActHealth.
2012;9:525–32.
59. Musgrave KO,Thornbury ME.Weight controlprogram for university
students conducted by nutrition seniors.J Am Diet Assoc.1976;68:462–6.
60. Pearman 3rd SN,Valois RF,Sargent RG,Saunders RP,Drane JW,Macera CA.
The impact of a required college health and physicaleducation course on
the health status of alumni.J Am CollHealth.1997;46:77–85.
61. Peterson S,Duncan DP,NullDB,Roth SL,GillL,Peterson S,et al.Positive
changes in perceptions and selections of healthfulfoods by college
students after a short-term point-of-selection intervention at a dining hall.
J Am CollHealth.2010;58:425–31.
62. Reed JA,Powers A,Greenwood M,Smith W,Underwood R,Reed JA,et al.
Using “point of decision” messages to intervene on college students’eating
behaviors.Am J Health Promot.2011;25:298–300.
63. Sallis JF,Calfas KJ,Nichols JF,Sarkin JA,Johnson MF,Caparosa S,et al.
Evaluation of a university course to promote physicalactivity:project GRAD.
Res Q Exerc Sport.1999;70:1–10.
64. Wadsworth DD,Hallam JS,Wadsworth DD,Hallam JS.Effect of a web site
intervention on physicalactivity of college females.Am J Health Behav.
2010;34:60–9.
65. Werch CE,Bian H,Moore MJ,Ames S,DiClemente CC,Weiler RM,et al.
Brief multiple behavior interventions in a college student health care clinic.
J Adolesc Health.2007;41:577–85.
66. Yakusheva O,Kapinos K,Weiss M,Yakusheva O,Kapinos K,Weiss M.Peer
effects and the freshman 15:evidence from a naturalexperiment.Econ
Hum Biol.2011;9:119–32.
67. Alpar SE,Senturan L,Karabacak U,Sabuncu N,Alpar SE,Senturan L,et al.
Change in the health promoting lifestyle behaviour of Turkish University
nursing students from beginning to end of nurse training.Nurse Educ Pract.
2008;8:382–8.
68. Ince ML,Ince ML.Use of a socialcognitive theory-based physical-activity
intervention on health-promoting behaviors of university students.Percept
Mot Skills.2008;107:833–6.
69. AfifiSoweid R,ElKak F,Major S,Karam D,Rouhana A,AfifiSoweid R,et al.
Changes in health-related attitude and self-reported behaviourof
undergraduate students atthe American university ofBeirutfollowing
a health awareness course.Educ Health.2003;16:265–78.
70. Skar S,Sniehotta FF,Molloy GJ,Prestwich A,Araujo-Soares V,Skar S,et al.
Do brief online planning interventions increase physicalactivity amongst
university students? A randomised controlled trial.PsycholHealth.
2011;26:399–417.
71. Tully MA,Cupples ME.UNISTEP (university students exercise and physical
activity) study:a pilot study of the effects of accumulating 10,000 steps on
health and fitness among university students.J Phys Act Health.2011;8:663–7.
72. Huang SJ,Hung WC,Chang M,Chang J,Huang S-J,Hung W-C,et al.The
effect of an internet-based,stage-matched message intervention on young
Taiwanese women’s physicalactivity.J Health Commun.2009;14:210–27.
73. Werch CE,Moore MJ,Bian H,DiClemente CC,Ames SC,Weiler RM,et al.
Efficacy of a brief image-based multiple-behavior intervention for college
students.Ann Behav Med.2008;36:149–57.
74. Von Ah D,Ebert S,NgamvitrojA,Park N,Kang DH.Predictors of health
behaviours in college students.J Adv Nurs.2004;48:463–74.
75. ButlerSM,Black DR,Blue CL,Gretebeck RJ.Change in diet,physical
activity,and body weightin female college freshman.Am J Health
Behav.2004;28:24–32.
76. Elfhag K,Rössner S.Who succeeds in maintaining weight loss? A
conceptualreview of factors associated with weight loss maintenance and
weight regain.Obes Rev.2005;6:67–85.
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