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Original article
The effectiveness of a 17-week lifestyle intervention on health behaviors
among airline pilots during COVID-19
Daniel Wilson
a,b,
*, Matthew Driller
c
, Ben Johnston
d
, Nicholas Gill
a,e
a
Te Huataki Waiora School of Health, The University of Waikato, Hamilton 3216, New Zealand
b
Faculty of Health, Education and Environment, Toi Ohomai Institute of Technology, Tauranga 3112, New Zealand
c
Sport and Exercise Science, Human Services and Sport, La Trobe University, Melbourne 3086, Australia
d
Aviation and Occupational Medicine Unit, Wellington School of Medicine, Otago University, Wellington 6242, New Zealand
e
New Zealand Rugby, Wellington 6011, New Zealand
Received 14 August 2020; revised 24 September 2020; accepted 15 October 2020
2095-2546/Ó2020 Published by Elsevier B.V. on behalf of Shanghai University of Sport. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract
Purpose: The aim of this study was to evaluate the efficacy of a 17-week, 3-component lifestyle intervention for enhancing health behaviors
during the coronavirus disease-2019 (COVID-19) pandemic.
Methods: A parallel-group (intervention and control) study was conducted amongst 79 airline pilots over a 17-week period during the COVID-19
pandemic. The intervention group (n= 38) received a personalized sleep, dietary, and physical activity (PA) program. The control group (n= 41)
received no intervention. Outcome measures for sleep, fruit and vegetable intake, PA, and subjective health were measured though an online sur-
vey before and after the 17-week period. The changes in outcome measures were used to determine the efficacy of the intervention.
Results: Significant main effects for Time £Group were found for International Physical Activity Questionnaire-Walk (p= 0.02) and for all
other outcome measures (p<0.01). The intervention group significantly improved in sleep duration (p<0.01; d= 1.02), Pittsburgh Sleep Qual-
ity Index score (p<0.01; d=1.01), moderate-to-vigorous PA (p<0.01; d= 1.32), fruit and vegetable intake (p<0.01; d= 3.11), Short-
Form-12v2 physical score (p<0.01; d= 1.84), and Short-Form-12v2 mental score (p<0.01; d= 2.69). The control group showed significant
negative change for sleep duration (p<0.01; d=0.47), Pittsburgh Sleep Quality Index score (p<0.01; d= 0.28), and Short-Form-12v2 mental
score (p<0.01; d=0.64).
Conclusion: Results provide preliminary evidence that a 3-component healthy sleep, eating and PA intervention elicit improvements in health
behaviors and perceived subjective health in pilots and may improve quality of life during an unprecedented global pandemic.
Keywords: COVID-19; Healthy eating; Lifestyle health; Moderate-to-vigorous physical activity; Sleep
1. Introduction
The global coronavirus disease-2019 (COVID-19) pan-
demic has rapidly spread, showing capability to infect the
world’s population.
1
Widespread infectious diseases such as
COVID-19 are associated with adverse mental health conse-
quences
2
and perturbations in physical activity (PA) behaviors
due to environmental factors such as forced self-isolation.
3
The confinement of individuals to their homes may increase
sedentary behavior
4
and has a direct impact on lifestyle, and,
consequently, on sleeping, eating, and PA patterns.
5
Further-
more, psychological and emotional responses to the pandemic
6
may lead to dysfunctional dietary and sleep behaviors.
7,8
Numerous industries have experienced substantial operational
perturbations emanating from COVID-19, including civil avia-
tion.
9
Consequently, these conditions may have unexplored
impacts on the health behaviors of airline pilots. Vocational
requirements of airline pilots present health risks, such as cir-
cadian disruption due to shift work and flight schedules,
10
fatigue induced by flight schedules,
11
irregular meal times,
mental stress demands associated with flight safety,
12
and the
sedentary nature of the job.
13
Circadian disruption is detrimen-
tal to acute physiological
14
and psychological
15
health metrics
and is associated with elevated risk for some chronic condi-
tions such as cardiovascular disease.
16
Despite reduced work-
loads for airline pilots during COVID-19,
9
substantial industry
disruption, uncertainty,
17
and financial concerns confounded
Peer review under responsibility of Shanghai University of Sport.
*Corresponding author.
E-mail address: Daniel.Wilson@toiohomai.ac.nz (D. Wilson).
https://doi.org/10.1016/j.jshs.2020.11.007
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Journal of Sport and Health Science 00 (2020) 18
www.jshs.org.cn
by lockdown conditions may present adverse effects on the
physical
3,18
and mental health
19
of pilots.
Obtaining adequate sleep, consuming enough fruits and
vegetables, and engaging in sufficient PA are 3 lifestyle behav-
iors that significantly reduce all-cause mortality
2022
and have
a positive effect on physical and mental health.
23,24
Good
sleep health facilitates the ability to maintain attentive wake-
fulness and is characterized by duration, quality, timing, and
efficiency.
25
Sleep duration guidelines proposed for adults
from 18 to 64 years is 79 h per night.
26
Fruit and vegetables
supply dietary fiber, vitamins and minerals, phytochemicals,
and anti-inflammatory agents.
27
Consumption of 400 g or more
of fruit and vegetables per day, excluding starchy vegetables,
is associated with protective effects against cardiovascular dis-
ease, some cancers,
28
depression,
29
and total mortality.
20
An
inverse association between fruit and vegetable intake and
mortality has been reported, with benefits observed in up to 7
daily portions.
30
Sufficient PA is defined as the achievement of
150 min/week or more of moderate-to-vigorous PA (MVPA),
or 75 min/week or more of vigorous-intensity PA, or an accu-
mulative equivalent combination of both, with added health
benefits of 300 or more total MVPA minutes per week.
31
Adequate sleep, healthy dietary behaviors, and sufficient
PA also play an important role in strengthening the immune
system and its antiviral defenses.
32,33
Lack of sleep, poor die-
tary habits, and physical inactivity are all independently asso-
ciated with immunocompromising effects,
32,34,35
which impair
host defenses against viral infection and may lead to individu-
als being at higher risk of more severe and complicated out-
comes than those which are non-immunocompromised.
36
A
lack of sleep,
37
dietary characteristics such as consuming a
Western diet,
38
and insufficient PA are each associated with
obesity,
39
which is suggested to be a profound risk factor for
adverse health outcomes from COVID-19.
40
Avoidance of health behaviors during a pandemic outbreak
may lead to immunocompromise, increased susceptibility to
viral propagation and elevated risk of severe symptoms.
36,41
Behavioral countermeasures for individuals are vital determi-
nants to health resilience amongst exposure to unprecedented
environmental events such as the COVID-19 pandemic.
5
Thus, evidence-driven interventions targeting the promotion
of behaviors that enable individuals to protect themselves
physically and psychologically during a pandemic are of pub-
lic health importance.
5,42
No previous studies have examined
change in health behaviors in airline pilots before and after a
pandemic event like COVID-19, nor have any studies evalu-
ated the effectiveness of a controlled lifestyle-based health
intervention during such times. The aim of this study was to
evaluate the effectiveness of a 3-component healthy eating,
sleeping and PA program in airline pilots during COVID-19
lockdown in New Zealand.
2. Methods
2.1. Design
A between-group, parallel controlled study with pre and
post-testing was performed to evaluate the effectiveness of a
17-week, 3-component lifestyle intervention for enhancing
health behaviors during a national COVID-19 pandemic
response in New Zealand.
During the 17-week intervention period, the first 5 weeks
preceded the New Zealand government’s enforcement of a
4-tier response system to COVID-19.
1
Thereafter, 5 weeks
were at alert Level 4 (March 25 to April 27, 2020), where all
non-essential workers were instructed to stay home, and safe
recreational activity was permitted only in the local area whilst
maintaining social distancing of 2 m or more. Subsequently,
2.5 weeks were at alert Level 3 (April 27 to May 14, 2020),
where some businesses could reopen; however, people were
instructed to work from home unless that was not possible.
Finally, 2 weeks were at alert Level 2 (May 14 to June 8,
2020), where gatherings of up to 100 people were allowed and
sport and recreation activities were also allowed. On June 8,
New Zealand returned to alert Level 1,
43
where within-com-
munity restrictions were removed yet international border
restrictions remained. Around the globe in the weeks following
the World Health Organization’s characterization of COVID-
19 as a pandemic on March 11, 2020, the airline industry expe-
rienced a decrease of approximately 60%80% in capacity at
major carriers.
9
Consequently, pilots experienced limited fly-
ing duties during the time when the intervention was con-
ducted (Table 1). Pre-testing occurred between February 14
and March 9, 2020, and post-testing was conducted between
June 8 and June 19, 2020. At pre- and post-testing, participants
completed an electronic survey measuring the following out-
come variables: self-report PA levels, dietary behaviors, qual-
ity and quantity of sleep, and subjective health.
2.2. Participants
The study population consisted of commercial pilots from a
large international airline. Seventy-nine pilots (aged 42 §
12 years, mean §SD, age, 65 male, 14 female) participated in
the study (Table 1). Participants were from a combination of
short haul, long haul, and mixed fleet rosters (n= 32, 35, and
12, respectively). Inclusion criteria were pilots who had a valid
commercial flying license and worked on a full-time basis.
Control group participants consisted of volunteers who were
pilots recruited at the time they completed their routine avia-
tion medical examinations at the airline medical unit during
the pre-test period (between February 14 and March 9, 2020).
The intervention group volunteered to participate in the life-
style intervention via self-selection. All volunteers participat-
ing in the study had responded to an invitation delivered to all
pilots within the company via internal organization communi-
cation channels. In the control group, mixed-fleet pilots had
the most flights, followed by long-haul and short-haul pilots
(10 §9, 7 §7, and 6 §5; respectively). In the intervention
group, mixed-fleet pilots had the most flights, followed by
short-haul and long-haul pilots (14 §1, 9 §9, and 6 §4,
respectively). All participants provided written informed con-
sent prior to participation in the study and were made aware
that they could withdraw from the study at any time should
they wished to do so. In order to support anonymity and
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2 D. Wilson et al.
dataset blinding during data analysis, participants were pro-
vided with a unique identification code on their informed con-
sent form and were instructed to input it into their survey
instead of their name. This study was approved by the Human
Research Ethics Committee of the University of Waikato in
New Zealand (reference number 2020#07).
2.3. Intervention group
Participants who registered their interest in participating in
the intervention and agreed to attend a face-to-face consulta-
tion session at the airline medical unit were included in the
intervention group. The intervention group received an initial
one-on-one 60-min consultation session with an experienced
health coach, followed by provision of an individualized health
program, weekly educational content emails during the inter-
vention and a mid-intervention phone call. The health advice
provided was evidence based and derived from experts in the
areas of PA, nutrition and chronobiology.
Personalized goal setting was carried out for each partici-
pant in the intervention group, with relevant outcome, perfor-
mance and process goals
44
discussed pertaining to each of the
3 intervention components: (1) dietary behaviors, (2) PA, and
(3) sleep habits. Moreover, individual perceived barriers to
health change were assessed with methods outlined else-
where
45
and were factored into the individualized program.
Sleep hygiene as an educational strategy has demonstrated
improvements in self-report sleep quality in blue collar
employees.
46
Stimulus control as a behavior technique has
demonstrated positive outcomes on sleep parameters in insom-
niacs.
47
An evidence-based sleep health checklist was devel-
oped for utilization in this study (Appendix). The items in the
checklist consisted of standard recommendations derived from
previous sleep hygiene and stimulus control studies.
48,49
Application of the items in the sleep health checklist involved
collaborative identification of the strategies that participants
were achieving at baseline. Pilots completed the Pittsburgh
Sleep Quality Index (PSQI) prior to attending their consulta-
tion. During the face-to-face consultation, the health coach dis-
cussed suboptimal PSQI component scores with the participant
and identified individual sleep priorities. Thereafter, partici-
pants collaboratively set personalized sleep practice goals with
support from the health coach. Personalized collaborative goal
setting was implemented as a behavioral technique to support
development of sleep habits that support restorative sleep.
44
PA prescription was individualized based on participant
perceived barriers and facilitators to exercise;
45
application of
the frequency, intensity, time, and type principles;
50
and pro-
gression to attainment of sufficient MVPA to meet guide-
lines
31
in congruence with individual capabilities. The
frequency and time of PA sessions were tailored to participant
time availability. Intensity was tailored based on participant
exercise experience, physical health, and goal orientation.
51
The type of PA was determined by the individual’s modality
preferences for cardiovascular (such as walking, running, or
cycling) and strengthening (e.g., resistance equipment and/or
bodyweight exercises) PA. The PA progression self-monitor-
ing was indicated, and participants were advised to implement
small, progressive changes in PA during the intervention (such
as increased session duration, more repetitions, greater exer-
cise intensity or more weekly bouts).
52
Healthy eating princi-
ples were emphasized through individualized advice and
educational materials focused on adding color to the diet via
consumption of fruit and vegetables;
27
choosing nutrient-dense
foods;
53
limiting processed foods; enhancing whole-food con-
sumption;
54
and reducing white carbohydrates, refined carbo-
hydrates, and added sugar (e.g., energy-dense food).
55
Relative to participant baseline behaviors, collaborative indi-
vidualized process behavior goals were established, for exam-
ple, adding color to meals and replacing high glycemic index
foods with low glycemic index options. The prescribed dose of
fruit was two or more servings per day, and the prescribed
dose of vegetables was three or more servings per day. A mid-
intervention (during Week 8 §1) follow-up phone call lasting
approximately 10 min consisted of a semi-structured interview
emphasizing discussion of progress and compliance pertaining
to individualized sleep, PA, and dietary goals established dur-
ing the pre-test consultation. Advice was provided when nec-
essary and was consistent with the advice given at pre-test.
Phone calls were used because they have been shown to sup-
port adherence to health interventions.
56
Congruent with evi-
dence-based methods previously outlined, weekly emails were
sent consisting of educational blog posts on varying topics
related to sleep health, PA, nutrition, and support for a healthy
immune system. Content was derived from health authorities
via publicly available information from the World Health
Organization and the Centers for Disease Control and Preven-
tion. During the COVID-19 lockdown, content was tailored to
pandemic conditions, including strategies for PA at home,
healthy recipes and immune system health information.
Table 1
Baseline demographic characteristics of participants (mean §SD; n).
Parameters All subjects (n= 79) Intervention (n= 38) Control (n= 41)
Sex (F/M) 14/65 8/30 6/35
Age (year) 42 §12 39 §10 44 §13
Short haul (n)32 22 10
Long haul (n)35 14 21
Mixed fleet (n)12 2 10
Flights during lockdown (n) 7.8 §7.3 5.9 §7.5 7.2 §7.1
Abbreviations: F = female; M = male.
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Lifestyle-based health intervention during COVID-19 3
2.4. Control group
The participants in the control group were blind to the inter-
vention and received no intervention or instruction regarding
health behaviors between pre- and post-tests. Control group
pilots were invited to voluntarily complete an electronic sur-
vey, and those who completed it during the previously defined
pre-testing period prior to COVID-19 lockdown were sent an
invitation via email to voluntarily complete the survey again
during the post-testing period in order to provide insight into
the effects of COVID-19 lockdown on their health behaviors.
2.5. Instruments
The PSQI was utilized to evaluate subjective sleep quality,
and scores were obtained before the start of the study at the
pre-test and were compared to scores obtained at the post-test
stage. The PSQI is a self-rated, 19-item questionnaire designed
to measure sleep quality and disturbances over a 1-month ret-
rospective period.
57
Sleep quality component scores are
derived for subjective sleep quality, sleep latency, sleep dura-
tion, habitual sleep efficiency, sleep disturbances, use of sleep-
ing medications, and daytime dysfunction, and collectively
produce a global sleep score.
57
Lower scores denote a healthier
sleep quality and range from 0 (no difficulties) to 21 (severe
sleep difficulties).
57
The PSQI has demonstrated good test-
retest reliability and validity and has been implemented in
many population groups.
57,58
The outcome measurements
were the change in global score between each group at post-
testing.
PA levels were assessed using the International Physical
Activity Questionnaire (IPAQ) Short Form, a validated self-
report measurement tool for MVPA that has been widely uti-
lized in large cohort studies, including New Zealand popula-
tion surveys.
59
The IPAQ Short Form estimates PA
achievement by quantifying weekly walking, as well as moder-
ate and vigorous PA duration and frequency. Responses were
used to compare participants’ PA levels with the health guide-
lines of 150 min of moderate-intensity PA or 75 min of vigor-
ous-intensity PA per week, or an equivalent combination of
MVPA per week.
31
IPAQ Short Form outcome measures
derived were (a) total weekly minutes of moderate + vigorous
PA in bouts of 10 min or more, excluding walking
(IPAQMVPA), and (b) total weekly minutes of walking in
bouts of 10 min or more (IPAQwalk). Responses were
capped at 3 h per day and 21 h per week, as recommended by
the IPAQ guidelines.
60
Fruit and vegetable intake were mea-
sured using 2 questions with acceptable validity and reliability
derived from the New Zealand Health Survey.
59
The questions
asked participants to report, on average, over the last week,
how many servings of fruit and vegetables they ate per day.
Responses to these questions were combined to determine total
daily fruit and vegetable intake.
Subjective self-report physical and mental health was deter-
mined using the Short Health Form 12v2 (SF-12v2), a short
version of the SF-36, which reduces the burden on participants
and has demonstrated a high correlation with SF-36 physical
and mental component summary scale scores.
61
The 12-item
survey produces a physical component summary scale
(PCS-12) and a mental component summary scale (MCS-12),
both of which have shown good test-retest reliability and con-
vergent validity in detecting changes in mental and physical
health over time in adults.
62
Scoring of the SF-12v2 was car-
ried out in accordance with standard summary scoring meth-
ods.
61
The summary scores are on a scale of 0100, with
clinical significance change scores suggested to be 510
points.
63
2.6. Statistical analyses
For all statistical analyses, raw data were extracted from the
Qualtrics online survey software (Qualtrics, Provo, UT, USA),
entered into an Excel spreadsheet (Microsoft, Seattle, WA,
USA) and then imported into the Statistical Package for the
Social Sciences (SPSS) (Version 26; IBM, New York, NY,
USA). Listwise deletion was applied for individual datasets
with missing values or participants who did not complete post-
testing. Stem and leaf plots were inspected to ascertain
whether there were any outliers in the data for each variable. A
Shapiro-Wilk’s test (p>0.05) and its histograms, QQ plots
and box plots were inspected for normality of data distribution
for all variables. Levene’s test was used to test homogeneity of
variance. Time-related effects within and between groups on
pre-test and post-test were assessed using ttests and repeated
measures mixed-design analysis of variance. Age, sex, and
number of flights were included as covariates in the analysis of
variance. Effect sizes were calculated using Cohen’s din order
to quantify between-group effects from pre-testing to post-test-
ing. Effect size thresholds were set at greater than 1.2, greater
than 0.6, greater than 0.2, and greater than 0.2, which were
classified as large, moderate, small, and trivial, respecitvely.
64
The alevel was set at a pvalue of less than 0.05.
3. Results
The demographic and baseline health characteristics
between the intervention and control groups are given in
Table 1. The attrition rates were 16% and 30% for the inter-
vention and control group, respectively. Intervention group
attrition was influenced by employment layoffs, whereas con-
trol group attrition was due to non-response to the online invi-
tation to voluntarily complete the survey at the post-test
period. In order to measure compliance, average sleep hours,
exercise sessions per week and daily fruit and vegetable con-
sumption was collected at the time of the mid-intervention
phone call. In the intervention group, 35 participants (92%)
were achieving 7.0 h or more of sleep per night and 3 (8%)
were achieving 6.9 h or less per night. For fruit and vegetable
servings per day, 36 participants (95%) were eating 5 or more
servings of fruit and vegetables per day, whereas 2 (5%) were
eating 24 servings per day. For MVPA, 33 participants
(87%) were completing 150 min or more of MVPA per week
and 5 (13%) were completing 149 min or less of MVPA per
week.
At baseline, the control group achieved significantly (p<
0.05) more sleep per night (36 min), a lower global PSQI score
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Please cite this article as: Daniel Wilson et al., The effectiveness of a 17-week lifestyle intervention on health behaviors among airline pilots during COVID-19, Journal of Sport and
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4 D. Wilson et al.
(1.8) (denoting better health), higher consumption of daily
fruit and vegetables (1.2 servings), a greater amount of weekly
walking (94 min), and higher SF-12v2 physical and mental
component scores (8.4 and 6.7, respectively). At baseline, the
control group exhibited an MVPA of 171 §78 min per week,
surpassing the MVPA recommended in the health guidelines
of 150 or more min per week,
31
whereas the intervention group
exhibited 116 §51 min per week of MVPA, which is beneath
the health guidelines threshold. However, the between-group
difference in MVPA was not statistically significant (p
0.05).
Group changes from pre-test to post-test are presented in
Table 2. Significant main effects for time £group were found
for IPAQ-Walk (p= 0.02) and for all other outcome measures
(p<0.01), which is associated with small to large effect size
differences between groups (Table 2). Significant main effects
for time were found for PSQI, fruit and vegetable intake,
PCS-12 and MCS-12 (p<0.01). Additional significant time
effects were found for hours slept and MVPA (p<0.05). The
within-group analysis revealed that the intervention elicited
significant improvements (p<0.01) in all health metrics at
post-test and IPAQ-walk (p= 0.02). The control group
reported a significantly higher PSQI score (p<0.01),
decreased hours of sleep and MCS-12 score (p<0.01), yet no
significant change was reported in other health metrics.
4. Discussion
To our knowledge, this study is the first controlled experi-
ment that has explored the effects of a lifestyle intervention on
health outcomes among pilots during a national pandemic
lockdown. This study aimed to improve health-related behav-
iors and promote positive change in subjective health of pilots
through personalized advice on healthy eating, sleep hygiene,
and PA. For most outcome measures, the controlled trial dem-
onstrated significant improvements in the intervention group
compared to the control group. These results are important in
order for researchers and health care professionals to provide
insight into potential health and quality-of-life perturbations
resulting from COVID-19 that may have potential implications
to flight safety. Furthermore, given the dearth of published
data pertaining to health behavior interventions during a pan-
demic and the limited availability of preventive lifestyle-based
interventions for pilots, our findings provide novel contribu-
tions to this field.
The average PSQI score for the intervention group
decreased (2.25), compared to a significant increase for the
control group (0.76). These results support previous studies
that used non-pilot populations, which have reported PSQI
score decreases of 1.54 to 1.8 following a sleep hygiene
education intervention
46,65
and 2.5 after a PA and sleep edu-
cation intervention based on a mobile health app.
66
An app-
based intervention to reduce fatigue in a pilot population
reported a smaller effect on PSQI score (0.59) after a
6-month intervention that focused on advice regarding day-
light exposure and sleep duration. None of these studies were
conducted under global pandemic conditions. A potential con-
founding factor to sleep quality and quantity improvements
during COVID-19 due to social isolation and lockdown con-
straints has been proposed,
67
where more time at home and
flexible sleepwake schedules may promote enhancements in
sleep. Furthermore, sleep disruption is an inherent risk for
pilots, and they are likely to have better sleep quality and
quantity when not at work.
Curiously, in our study the control group significantly
increased its PSQI score. Similar findings have been reported
elsewhere in a general-population-based study in Australia
(n= 1491), which reported that 40.1% of the participants indi-
cated a negative change in sleep quantity during lockdown.
8
In
another study, sleep quantity improved while sleep quality was
degraded in Austrian adults (n= 435).
68
In that study, an
increase in subject burden and decreased physical and mental
wellbeing were also observed. Cognitive states of elevated dis-
tress and emotional disturbances have been associated with
unhealthy dietary patterns and poor diet quality and may
impair health behavior motivation.
5
Researchers have advo-
cated for implementation of strategies to mitigate the effects
of lockdown on sleep quality, including obtaining sufficient
PA, exposure to natural daylight,
68
and well-balanced meals
rich in vitamins and minerals.
5
Our study findings support
these messages in that we observed significant improvements
in PCS-12 and MCS-12 scores among the intervention group
Table 2
Changes in health behaviors from baseline to post-test at 17 weeks (mean §SD).
Intervention group Control group ANOVA
(time £group interaction)
Effect size
Pre Post Change Pre Post Change pd
Hours slept (h:mm) 7:00 §0:54 7:48 §0:48
**
0:48 §0:54 7:36 §0:48 7:12 §1:00
**
0:24 §0:42 <0.01 1.35, Large
PSQI global 6.4 §2.7 4.1 §1.8
**
2.3 §2.4 4.5 §2.5 5.3 §2.9
**
0.8 §0.9 <0.01 1.14, Large
IPAQ-walk 61 §69 93 §96 32 §105 155 §135 136 §111 19 §79 0.02 0.45, Small
IPAQ-MVPA 116 §51 201 §77
**
85 §100 171 §78 146 §75 26 §82 <0.01 1.44, Large
Fruit and vegetable intake 3.0 §0.6 6.1 §1.7
**
3.1 §1.5 4.2 §0.9 4.1 §1.5 0.1 §1.3 <0.01 2.09, Large
PCS-12 43.3 §5.2 52.6 §4.9
**
9.4 §5.5 51.7 §5.7 51.5 §6.0 0.2 §2.2 <0.01 1.52, Large
MCS-12 48.0 §4.0 54.8 §1.0
**
6.8 §4.1 54.7 §4.3 51.9 §4.5
**
2.8 §4.4 <0.01 2.09, Large
d= Cohen’s d effect size, effect threshold. *p<0.05, **p<0.01.
Abbreviations: ANOVA = analysis of variance; IPAQ = International Physical Activity Questionnaire; MCS-12 = SF-12v2 Mental Component Summary Scale;
MVPA = moderate-to-vigorous physical activity; PCS-12 = SF-12v2 Physical Component Scale; PSQI = Pittsburgh Sleep Quality Index; SF-12v2 = Short Health Form 12v2.
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Please cite this article as: Daniel Wilson et al., The effectiveness of a 17-week lifestyle intervention on health behaviors among airline pilots during COVID-19, Journal of Sport and
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Lifestyle-based health intervention during COVID-19 5
compared to the control group, after implementation of a
3-component healthy sleep, eating and PA intervention during
an unprecedented global pandemic.
The average MVPA and fruit and vegetable consumption
significantly increased in our intervention group, compared to
no significant change in the control group. The intervention
group increased MVPA from 116 min to 201 min at post-test-
ing, which crossed the MVPA guideline threshold of 150 min
or more per week.
31
Conversely, the control group decreased
MVPA from 171 min to 146 min per week at post-testing,
decreasing to below the guideline threshold. Both the control
and intervention groups did not achieve the recommendation
of 5 or more servings per day for fruit and vegetable intake at
baseline.
69
The intervention group elevated its intake per day,
achieving the guideline threshold at post-testing. Our study
findings suggest that the 3-component intervention supported
achievement of PA and fruit and vegetable guideline thresh-
olds and significantly improved PCS-12 and MCS-12 scores in
the intervention group. Furthermore, the intervention appeared
to mitigate decay in both SF-12v2 summary scales, which
were observed in the control group.
Research exploring the relationships among COVID-19, PA
and dietary behaviors have yielded mixed outcomes. Within an
Italian population (n= 3533) during COVID-19 lockdown, simi-
lar proportions of the participants stated that they ate less or had
better diets (35.8% and 37.4%, respectively) in regard to intake
of fruit, vegetables, nuts, and legumes.
7
Furthermore, their PA
behaviors did not significantly change; however, a greater
amount of exercise was completed at home.
7
In a study with
Australians participants, 48.9% expressed a negative change in
PA during lockdown and also reported that negative changes in
PA and sleep were associated with expression of higher anxiety,
depression and stress levels.
8
In a Canadian sample (n= 1098),
those who engaged in more outdoor PA time during lockdown
had lower anxiety levels than those who did not. The
COVID-19 lockdown in New Zealand at Levels 34 presented
barriers for engaging in PA, such as social distancing, travel
restrictions and inaccessibility to parks, gyms, and other recrea-
tional facilities, which may have promoted sedentary behavior
and contributed to the decline in PA observed in the control
group.
4,17
Other studies found that life stressors, including job
uncertainty,
9
anxiety and psychological stress,
2
financial loss
and disconnection with community and nature may have
impacted health behaviors during this time.
17
In contrast, the
reduced time at work has been suggested as a potential facilita-
tive factor in enhancing health behaviors during lockdown,
67
because this naturally alleviates one of the most commonly
expressed barriers to engagement in PA: a lack of time.
A limited number of studies have investigated the efficacy
of interventions targeting healthy dietary and PA behaviors
among pilots. A study of an app-based, 6-month intervention
using a pilot population reported significant improvements in
their weekly moderate and strenuous activity (0.21 and
0.19 days per week, respectively), as well as a reduction in
their snacking behavior (0.88 servings per duty).
70
Consulta-
tions with pilots on their diet and physical exercise behaviors
yielded a positive change in their blood lipids and body mass
index.
12
Our findings pertaining to MVPA, fruit and vegetable
intake, PSQI and SF-12v2 among pilots provide promising
preliminary outcomes regarding the effects of a 3-component
intervention and warrant further investigation with objective
measures of outcomes.
The differential recruitment strategies and limited exclusion
criteria for the intervention and control groups are limitations
that may have contributed to the significant differences
observed at baseline for sleep quantity and PSQI score, IPAQ-
walk, MVPA, fruit and vegetable consumption and SF-12v2
subjective health scores, with superior results in favor of the
control group. Thus, it is recommended that future research
studies have more robust randomization assignment conditions
for participant allocation to groups in order to increase the
probability of capturing the true population average and
enhance the generalizability of findings. Future research
should also increase the sample size, given the apparent var-
iances in health behaviors amongst the pilot population, which
in itself warrants further investigation in order to characterize
these variances.
Future research with pilot populations that compare single-
behavior to multiple-behavior interventions would provide
valuable insight into the magnitude of the effects when these
differing intervention approaches are used. Given the bidirec-
tional relationship between sleep, nutrition and PA and some
evidence to suggest multiple-component interventions may
elicit stronger participation and adherence,
71
we suggest future
research examine more time-efficient and scalable strategies
for implementation of a 3-component sleep, nutrition and PA
program. For feasibility reasons, self-report methods were uti-
lized in this study, and the limitations of this approach have
been discussed elsewhere.
72
To enhance outcome measure
validity and reliability, it would be preferrable to use objective
measurement methods such as actigraphy to monitor sleep and
PA and photo logging of dietary behaviors to quantify health
behavior metrics. Comparisons of our study to related studies
are limited because most other studies were conducted under
normal societal conditions while ours was conducted under
pandemic conditions.
5. Conclusion
Behavioral countermeasures for individuals are vital deter-
minants of health resilience during exposure to unprecedented
environmental events such as the COVID-19 pandemic.
5
The
attainment of sleep, fruit and vegetable intake and PA guide-
lines is associated with increased physical and mental
health,
24,29
enhanced immune defenses,
33
and a reduction in
the risk of obesity.
39
Evidence-based interventions targeting
the promotion of these behaviors will enable individuals to
protect themselves physically and psychologically during a
pandemic, and therefore are of immense public health impor-
tance.
5,42
The 3-component healthy sleep, eating, and PA
intervention implemented in this study elicited significant
improvements in sleep quality and quantity, fruit and vegetable
intake, and MVPA and suggests that achieving these 3 guide-
line thresholds promotes mental and physical health and
ARTICLE IN PRESS
Please cite this article as: Daniel Wilson et al., The effectiveness of a 17-week lifestyle intervention on health behaviors among airline pilots during COVID-19, Journal of Sport and
Health Science (2020), https://doi.org/10.1016/j.jshs.2020.11.007
6 D. Wilson et al.
improves quality of life among pilots during a global pan-
demic. Our study of this intervention provides preliminary evi-
dence that a low-intensity, multi-behavior intervention may be
efficacious during a pandemic and that similar outcomes may
be transferrable to other populations. However, more robust
recruitment methods are required to confirm our findings and
increase their generalizability.
Acknowledgments
The authors wish to thank the pilots for participating in this
study.
Authors’ contributions
DW and NG participated in conceptualization of the study
and data collection; DW, MD, BJ, and NG contributed to the
design of the study, data analysis, interpretation of the results
and manuscript writing. All authors have read and approved
the final version of the manuscript, and agree with the order of
presentation of the authors.
Competing interests
The authors declare they have no competing interests.
Appendix
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8 D. Wilson et al.
