Daily Step Counts from the First Thailand National Steps Challenge in 2020: A Cross-Sectional Study

The association between health costs and physical inactivity; analysis from the Physical Activity at Work study in Thailand

Introduction

Physical inactivity increases the risks of several common yet serious non-communicable diseases, costing a tremendous amount of health expenditure globally. This study aimed to estimate the association between health costs and physical inactivity in Thailand.

Methods

Data from the Physical Activity at Work cluster randomized controlled trial participants with valid objective physical activity data were extracted. Health costs were collected using the Health and Welfare Survey and the Work Productivity and Activity Impairment Questionnaire and were categorized into past-month outpatient illness, past-year inpatient illness, and past-week presenteeism and absenteeism. Time spent in moderate-to-vigorous physical activity was used to determine the activity level according to the current guideline (i.e., ≥150 minutes moderate-intensity or ≥75 minutes vigorous-intensity equivalent physical activity per week). The primary analysis evaluated the association between direct cost (treatment and travel costs) and societal cost (direct cost plus absenteeism due to the illness) of past-month outpatient illness and physical inactivity using a two-part model.

Results

In total, 277 participants with a mean age of 38.7 were included. Average direct and societal cost due to past-month outpatient illness were 146 THB (3.99 USD) (SD = 647 THB) and 457 THB (12.5 USD) (SD = 1390 THB), respectively. Compared to active participants, direct and societal cost of past-month outpatient illness were 153 THB (4.18 USD) (95%CI: -54.7 to 360 THB) and 426 THB (11.7 USD) (95%CI: 23.3 to 829 THB) higher in physically inactive individuals, respectively, adjusted for covariates. The additional societal cost of past-month outpatient illness was 145% higher in physically inactive participants compared to active participants. On the other hand, there was no significant association in direct and societal cost of past-year inpatient illness nor past-week indirect costs between physically active and non-active participants.

Discussion

Results were similar to recent findings in different countries. However, the findings should be generalized with caution due to the small sample size and potential bias from reverse causation. Future research is crucial for clarifying the health costs of physical inactivity in Thailand and other countries.

The physical activity at work (PAW) study: a cluster randomised trial of a multicomponent short-break intervention to reduce sitting time and increase physical activity among office workers in Thailand

Background

Sedentary behaviour increases the risks of non-communicable diseases. The objective of this trial was to evaluate the effect of the Physical Activity at Work multicomponent intervention to reduce sedentary behaviour in Thai office workers.

Methods

Offices under the Ministry of Public Health Thailand, were randomly allocated to the intervention and control group in a 1:1 ratio, stratified by office size. The intervention included individual (pedometer and lottery-based financial incentives), social (group movement breaks), environmental (posters), and organisational (leader encouragement) components. At baseline and 6-month follow-up, participants wore ActiGraph^TM on the waist for ten days. The primary outcome was the between-group difference in sedentary time at 6-month, analysed using a linear mixed-effects model. Other outcomes were physical activity, biomarkers, productivity, and musculoskeletal health. Trial registration: The PAW study was registered at the Thai Clinical Trials Registry (ID TCTR20200604007) on 02 June 2020.

Findings

282 office workers were recruited and randomly allocated to the control group (142 participants, nine offices) and the intervention group (140 participants, nine offices). The mean age was 38.6 years (SD = 10.4), and 81% were women. There was no evidence of intervention effects on sedentary time during waking hours (-26.8; 95% CI = -69.2 to 15.7 min), physical activity levels, or biomarkers between groups at 6-month. In the adjusted analysis, increases in time spent in moderate-to-vigorous physical activity (5.45; 95% CI = -0.15 to 11.1 min) and step count (718; 95% CI = -45 to 1481 steps) during waking hours were observed, although there was no evidence of a difference between groups.

Interpretation

The intervention did not significantly reduce sedentary time in Thai office workers. Suboptimal intervention uptake due to Covid-19 pandemic restrictions and loss of statistical power associated with recruitment constraints may explain this result. Further investigations are needed to evaluate the processes of the trial.

Funding

The Thai Health Promotion Foundation and the International Decision Support Initiative (iDSI).

mHealth interventions targeting movement behaviors in Asia: A scoping review

mHealth interventions can promote healthy movement behaviors (physical activity, sedentary behavior, and sleep). However, recent reviews include few studies from Asia, despite it being home to over 60% of the world population. The aim is to map the current evidence for mHealth interventions targeting movement behaviors in Asia. Six databases were searched up until August 2021. Included studies described an mHealth intervention targeting one or more movement behaviors, delivered in a country/territory in Asia, to a general population. A total of 3986 unique records were screened for eligibility in duplicate. Eighty studies with 1,413,652 participants were included. Most were randomized (38.8%) or quasi-experimental (27.5%) trials. Studies were from 17 countries/territories (out of 55); majority were high- (65.0%) or upper middle-income (28.7%). Physical activity was targeted most often (93.8%), few targeted sedentary behavior (7.5%), or sleep (8.8%). Most targeted one movement behavior (90.0%), and none targeted all three together. Interventions typically incorporated a single mHealth component (70.0%; app, pedometer, text messages, wearable) and were delivered remotely (66.3%). The average intervention length was 121.8 (SD 127.6) days. mHealth interventions in Asia have primarily targeted physical activity in high- and upper middle-income countries. There are few interventions targeting sedentary behavior or sleep, and no interventions in low-income countries.

Association Between Physical Activity and Type 2 Diabetes Using the International Physical Activity Questionnaires: A Case-Control Study at a Health Promoting Hospital in Chiang Mai, Northern Thailand

BACKGROUND

Health education and promotion is active in Thailand where diabetes is prevalent at 11.6% of the general adult population in 2021.

PURPOSE

This study aimed to describe and compare the levels of physical activity between patients with newly diagnosed diabetes and non-diabetic controls in northern Thailand.

METHODS

This observational case-control study included participants aged between 25 and 74 years in Chiang Mai. We recruited 150 patients with type 2 diabetes mellitus (T2DM) at Sanpatong District Hospital and 150 control participants (non-T2DM) in the community. Interviews were conducted using the International Physical Activity Questionnaires-Short Form. Anthropometric measurements and social demographic information were collected from both patients and controls in 2019.

RESULTS

The mean age of the participants was 58.8 ± 8.4 years in the T2DM group and 56.5 ± 9.9 years in the non-T2DM group. Compared to controls, patients with T2DM had received significantly more physical activity education (P < 0.001, Fisher's test). Most cases (93.3%) had received such education at a hospital or health center. The median total metabolic equivalents (METs) minutes per week (min/week) for participants in the T2DM group were higher than those in the non-T2DM group (2726 vs 1140 METs min/week) (P < 0.001, Mann-Whitney test). Comparing the case and control groups in the category of PA level, we found that the case group had a higher proportion of high-level physical activity (P < 0.001, chi-square test).

CONCLUSION

Diabetes patients attending a community hospital exhibited high levels of physical activity. The majority of them received education related physical activity from a primary health care service.