Combined diet and physical activity is better than diet or physical activity alone at improving health outcomes for patients in New Zealand’s primary care intervention

R E S E A R C H A R T I C L E Open Access
Combined diet and physical activity is
better than diet or physical activity alone at
improving health outcomes for patients in
New Zealand’s primary care intervention
Catherine Anne Elliot * and Michael John Hamlin
Abstract
Background: A dearth of knowledge exists regarding how multiple health behavior changes made within an
exercise prescription programme can improve health parameters. This study aimed to analyse the impact of
changing diet and increasing exercise on health improvements among exercise prescription patients.
Methods: In 2016, a representative sample of all enroled New Zealand exercise prescription programme (Green
Prescription) patients were surveyed (N = 1488, 29% male, 46% ≥ 60 yr). Seven subsamples were created according
to their associated health problems; metabolic (n = 1192), physiological (n = 627), psychological (n = 447), sleep
problems (n = 253), breathing difficulties (n = 243), fall prevention (n = 104), and smoking (n = 67). After controlling
for sex and age, multinomial regression analyses were executed.
Results: Overall, weight problems were most prevalent (n = 886, 60%), followed by high blood pressure/risk of
stroke (n = 424, 29%), arthritis (n = 397, 27%), and back pain/problems (n = 382, 26%). Among patients who
reported metabolic health problems, those who changed their diet were 7.2, 2.4 and 3.5 times more likely to lose
weight, lower their blood pressure, and lower their cholesterol, respectively compared to the control group.
Moreover, those who increased their physical activity levels were 5.2 times more likely to lose weight in comparison
to controls. Patients who both increased physical activity and improved diet revealed higher odds of experiencing
health improvements than those who only made one change. Most notably, the odds of losing weight were much
higher for patients changing both behaviours (17.5) versus changing only physical activity (5.2) or only diet (7.2).
Conclusions: Although it is not currently a programme objective, policy-makers could include nutrition education
within the Green Prescription initiative, particularly for the 55% of patients who changed their diet while in the
programme. Physical activity prescription with a complimentary nutrition education component could benefit the
largest group of patients who report metabolic health problems.
Keywords: Primary care intervention, Physical activity, Exercise prescription, Disease prevention, Diet, Metabolic
health, Physiologic, Psychologic, Behavior change, Nutrition
* Correspondence: [e-mail]
Department of Tourism, Sport and Society, Lincoln University, PO Box 85084,
Lincoln, Christchurch, Canterbury 7647, New Zealand
© The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. 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.
Elliot and Hamlin BMC Public Health (2018) 18:230
https://doi.org/10.1186/s12889-018-5152-z

Background
A lack of physical activity, tobacco smoking and an
unhealthy diet contribute to almost 80% of the world’s
risk of cardiovascular disease and type 2 diabetes [1]. Po-
sitioned as the leading cause of premature death globally
[2], cardiovascular disease is an epidemic driven by type
2 diabetes and the metabolic syndrome [3]. Empirical
evidence suggests that the co-occurrence of behavioral
risk factors yield greater risks for chronic diseases than
the sum of their individual independent effects [4, 5].
For instance, individuals who are diagnosed with meta-
bolic syndrome show a 50-60% higher risk of having a
cardiovascular disease than those without metabolic syn-
drome [6]. With an estimated 20-25% of the world’s
adult population presenting metabolic syndrome [3],
multiple disease risk factors are increasingly common in
adults [7].
Major risk factors of cardiovascular disease and meta-
bolic syndrome are physical inactivity and poor diet [8]
with physical inactivity positioned as the primary cause
of most chronic diseases [9]. Although compelling
evidence exists for the efficacy of improving physical
activity and diet [10] in treating individuals with multiple
risk factors [11], usual care relies on pharmacotherapies
which merely address disease symptoms [12].
Cardiovascular disease is the number one single cause
of death in New Zealand, accounting for 33% per annum
[13]. In 1998, New Zealand actively addressed this con-
cern by initiating a primary-care intervention strategy
called Green Prescription, whereby general practitioners
and practice nurses refer or prescribe eligible patients to
trained personnel [14]. Nearly 40,000 Green Prescription
referrals were written by clinicians in New Zealand from
2013 to 2014 [15]. Green Prescription patients might
receive an exercise prescription for any combination of
cardiorespiratory, metabolic, physiological or psycho-
logical reasons. Once enroled, patients meet with physical
activity specialists who customise a physical activity rou-
tine which is catered to the patients’ needs and lifestyles
while addressing barriers such as asthma, injury, back
pain, etc.
The Green Prescription Programme is akin to a
globally adopted health initiative called Exercise is
Medicine. Since both programmes focus on increasing
physical activity a as means of chronic disease
prevention, there is little scope to focus on the nutri-
tional component of the energy balance equation.
Nevertheless, 68% of survey respondents reported
they have received information on healthy eating
through Green Prescription. Additionally, 55% of
patients in the subsamples analysed in this study
reported changing diet as well as physical activity.
From a physiological perspective, the energy balance
behaviors of increasing physical activity and changing
diet are major preventive therapies, particularly for
weight loss, [10, 16] but also for metabolic syndrome
[11] and cardiovascular disease [17]. Evidence sug-
gests an increased likelihood of weight loss when
multiple health behavior changes are implemented
compared to one [10, 16, 18]. From a behavioral and
motivational self-regulation standpoint, the synergistic
effects of improving diet and physical activity have
been investigated. A study from Mata et al. [19]
showed that physical activity self-determination
predicted eating self-regulation and fully mediated the
relationship between physical activity and eating self-
regulation during a lifestyle weight-management
programme [19]. This suggests that psychological
mechanisms involved in motivation may help explain
the association between physical activity and eating
behaviors. Nevertheless, there is a dearth of know-
ledge regarding the effects of multiple health behavior
changes by exercise prescription patients to improve
metabolic, physiological and psychological outcomes.
This study aimed to analyse the impact of changing
diet and increasing exercise on health improvements
among exercise prescription patients.
Methods
The ethics application for this study was considered and
subsequently waived by the Health and Disability Ethics
Committees in New Zealand due to the research being
an evaluation of an existing programme. Responses were
collected on an informed consent basis as part of the
17th annual Green Prescription patient survey. The
survey was administered by Research New Zealand as
contracted by the NZ Ministry of Health to measure the
performance of Green Prescription.
This mixed-method online, telephone and paper-based
survey was conducted from March-May 2016 using a
stratified random sample. Green Prescription patients
who had contact with one of the 17 Green Prescription
contract holders in all District Health Boards over 6
months from July-December 2015 were eligible for
sampling.
Sample
Contract holders throughout New Zealand, who are re-
sponsible for delivering the national Green Prescription
Programme, submitted their patient list to Research
New Zealand, totaling 18,849 Green Prescription
patients throughout the country. Historically, there have
been lower survey response rates among minority groups
enroled in Green Prescription, namely, Māori and Pacific.
Assuming a low response rate, an oversampling of these
groups was executed to help ensure a more ethnically-
representative sample of patients. In the total sample,
European New Zealander respondents comprised 59%,
Elliot and Hamlin BMC Public Health (2018) 18:230 Page 2 of 10

Māori 28% and Pacific 13%. The first step in the data
collection process entailed separating larger contract
holders (with > 700 patients) from smaller contract
holders. A sample of n = 2440 Māori and Pacific
patients was randomly selected from the combined
lists of the larger contract holders, proportional to
the total number of Māori and Pacific patients on
these lists. All patients with known contact details on
the lists of smaller contract holders (n = 4560) were
also selected. Finally, a random sample (n = 3000)
was selected from the remaining lists of the larger
contract holders in proportion with the total number
of non-Māori/Pacific patients.
On 7th March 2016, selected patients were sent a
letter from Research New Zealand inviting them to
participate, along with a paper copy of the survey, and a
reply-paid envelope with three $250 gift vouchers used
as incentive. The letter introduced the survey and its
purpose and gave instructions for completing the survey
on paper or online. On 30 March 2016, 4657 patients
who had not yet responded were sent a reminder letter
and 1052 were sent a reminder email. Commencing 30
April 2015, a reminder call was made to all non-
responding Māori and Pacific patients (n = 1973), and
non-Māori and Pacific patients (n = 960). Of these, 1478
were contacted during the reminder call period (each
was called a maximum of five times). The main survey-
ing period ended on 15 May 2016.
To account for the varying sampling criteria applied to
large and small contract holders and the different participa-
tion rates, the results were weighted to be representative of
the proportion of patients from each contract holder. The
weighted results for the total sample have a maximum mar-
gin of error of plus or minus 1.8%, at the 95% confidence
level (p. 15) [20].
Participation rate
A representative sample of 10,000 patients were invited
to complete the survey. A total of n = 2843 valid, com-
pleted responses were received during the survey period
(n = 2045 paper, n = 496 online, and n = 302 telephone),
representing a participation rate of 28% [20]. Data was
screened according to the flow diagram in Fig. 1.
Patients reporting they were temporarily off of (n = 448)
or were no longer following Green Prescription physical
activities (n = 423) and those who didn’t respond to this
item (n = 134) were excluded from analysis. Those
included in analysis were either still following Green
Prescription physical activities (n = 1160) or they were
engaging in a physical activity different from their Green
Prescription recommendations (n = 678). Patients who
reported receiving a Green Prescription for “heart prob-
lems” (n = 202), “injury/surgery recovery” (n = 202) and/
or “other” (n = 258) were excluded from analysis. These
reasons could have prevented or hindered patients’ abil-
ity to engage in physical activity. In total, “1488 surveys
were analysed, comprising 17% of participants being first
prescribed a Green Prescription less than 4 months ago,
28% 4-6 months ago, 22% 6-8 months ago and 33%
more than 8 months ago.” Table 1 displays the sex, age
and ethnicity of all patients used for analysis after the
data screening.
Fig. 1 Flow diagram showing patient inclusion (box) and exclusion (dotted box) criteria for assessment
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