Background
The negative effects of sedentary behaviour (SB) and a lack of physical activity (PA) on health have been well documented [
1‐
8]. SB is defined as any waking time activity during which one is seated, reclined or lying, having an energy expenditure ≤1.5 metabolic equivalents (METs), while PA is defined as any activity with an energy expenditure > 1.5 METs [
9‐
11]. High levels of SB are associated with a 112% increase in the risk of diabetes, 147% increase in the risk of cardiovascular disease, 90% increase in the risk of cardiovascular mortality and 49% increase in the risk of all-cause mortality [
4]. In addition, SB has detrimental associations with fasting glucose, fasting insulin, triglycerides, high-density lipoprotein cholesterol and waist circumference [
1].
The negative effects of the behaviour have also been studied in Thailand. According to recent estimates, 6.3% of all-cause mortality in Thailand is due to physical inactivity [
12]. The estimated total healthcare costs from physical inactivity in Thailand accounted for $190 million in international dollars (INT$ was calculated using purchasing power parity conversion factors from 2013) [
13]. The proportion of individuals not meeting 150 min of moderate-to-vigorous PA in Thailand have increased from 18.5% in 2008 to 19.2% in 2014 [
14]. According to the Thai Health Promotion Foundation, Thais spend on average 2 h a day engaging in PA and about 13 h in SB [
14].
A long-studied effect of urbanisation is the transition from jobs with more manual work (such as agriculture) to non-manual service jobs that are typically desk-bound [
15]. Typical office workers spend most of their SB hours at the office. This is particularly true for computer-based occupations, where employees spend a substantial amount of time in uninterrupted sitting [
16‐
18]. A study found that office-based workers spent up to 75.8% of their working time sitting [
19]. Further, breaks between these sitting times were uncommon, with 25% of the total sitting time in bouts of 55 or more minutes [
17]. This directly translates to a lower energy expenditure, where such workers expended around ~ 700 kcals/day, compared to individuals whose jobs require some manual labour (~ 2300 kcals/day) [
20]. As work-time contributes significantly to the total sedentary time, working hours are an important avenue to address movement behaviours.
It has been suggested that one way to attenuate the negative effects of SB is to increase PA. Studies have illustrated that after adjusting for PA, the negative associations with SB were less pronounced [
2,
5]. Physical inactivity represents the non-achievement of PA guidelines, and based on the World Health Organisation global recommendations on PA for health state, adults should do at least 150 min of moderate-intensity aerobic PA throughout the week [
21]. Having short PA breaks during working hours can help office workers meet these recommendations.
Short break interventions in the workplace have shown reductions in sedentary time [
22]. However, mixed results have been found for their impact on intermediate health outcomes such as calories spent, cholesterol (HDL-C and LDL-C), triglycerides, fasting blood glucose, blood pressure and stress level [
22‐
30]. Importantly, results of a recent randomised trial showed that taking two long breaks (15 min) per workday is less effective than taking shorter breaks (1-2 min) every 30 min [
22,
24]. In this study, the long-break group had no change in health outcomes while the short-break group had small-to-moderate declines in total cholesterol (d = − 0.33;
p = 0.10), triglycerides (d = − 0.38;
p = 0.06), and fasting blood glucose (d = − 0.29,
p = 0.01). Even though short breaks every half an hour seems to be more clinically effective, it is less likely to be feasible and scalable in real world practice. Moreover, the above studies were conducted only in high-income countries. No study has investigated the effects of a short-break intervention on the reduction on SB and its impacts on health and productivity outcomes at the workplace in low- and middle-income countries where the majority of metabolic diseases occurs. This study aims to fill this gap.
The study is designed as a two parallel-group cluster randomised superiority trial. The primary outcome assesses sedentary time at the 6th month. The aims of the study are to evaluate (i) the impact of a multicomponent short-break office intervention on minutes spent sedentary during office hours. In addition, the study will also evaluate the effect of the intervention on secondary outcomes such as PA, cardiometabolic risk factors and productivity (ii) the sustainability of the behavioural change; and (iii) the cost-effectiveness of the short-break office intervention. The cost-effectiveness analysis will allow the results to be compared with other trials’ economic evaluations. The results of this study will assist the Thai government in developing health promotion and disease prevention benefit package under the Universal Healthcare Coverage (UHC) scheme. Filling this knowledge gap might also help inform investments on short break interventions in the private sectors.
Discussion
This paper describes the design of a cluster randomised trial that will evaluate the effects of the multicomponent PAW behavioural intervention on SB and other outcomes in desk-based office workers in a low- and middle-income country. This type of studies in a given setting is very rare in the current literature. The PAW intervention builds on the previous effort of the MOPH, and previous experiences of the research team in behavioural health interventions focused on SB and PA, as well as movement behavior monitoring [
50‐
53]. Others have shown that activity accelerometers, together with financial incentives, are promising environmental intervention to reduce occupational sitting time and increasing PA at least in the short-term [
54] and possibly also in the longer term.
This evaluation will identify changes in key movement behaviours via Fitbit real-time data, as well as objective measures via ActiGraph on time spent in sedentary, light, moderate or vigorous activities as well as step counts, intermediate health outcomes as well as work-related outcomes. We will also include policy-relevant economic evaluation through both a Markov model and person-level cost-effectiveness analysis to report a short-term health and economic impact of the PAW program using the data from the trial within the study period. These will be used to formulate recommendations for future improvement and refinement of the intervention, which will be essential in the light of the potential wider implementation and roll out by the MOPH.
Potential difficulties and limitations and alternative approaches
Identification of effect sizes might be indirect for data with repeated measures. As such, care will be taken to use alternative estimation techniques such as multilevel linear mixed-effect model and adjusted standard errors to ensure robust results from treatment effects when evaluating the impact of the interventions. We may not be able to follow people for a prolonged period due to loss to follow-up.
In conclusion, the current cluster randomised controlled trial will assess the effects of a multicomponent PAW behavioural intervention in reducing sitting time and increasing PA in desk-based office workers in the longer-term as compared to usual practice. In addition, from a company and societal perspective, we will provide insight into the cost-effectiveness of the intervention as compared to usual practice. We will also assess if a reduction in sitting time and increase in PA is related to the quality of life, health and work-related outcomes, and how the PAW intervention can be further improved.
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