Prevalence of sufficient MVPA among Thai adults: pooled panel data analysis from Thailand's surveillance on physical activity 2012-2019

Association of the Combination of Moderate-to-Vigorous Physical Activity and Sleep Quality with Physical Frailty

BACKGROUND

The association of the individual and combined effects of moderate-to-vigorous physical activity (MVPA) and sleep quality with physical frailty in community-dwelling older adults is still unknown.

SUBJECTS AND METHODS

A cross-sectional study was conducted with a sample of older adults who had not required nursing care or support services. Physical frailty was assessed using Liu's definition based on Fried's concept. MVPA was measured by a triaxial accelerometer, and individuals who met either moderate physical activity (MPA) for ≥300 min/week, vigorous physical activity (VPA) for ≥150 min/week, or both were defined as "MVA+". "SLP+" was defined as a Pittsburgh Sleep Quality Index score of <5.5 points.

RESULTS

A total of 811 participants were included in the final analysis. After adjusting for the multivariable confounding factors, the odds ratios (ORs) and 95% confidence intervals (CIs) for physical pre-frailty and frailty in the MVA-SLP+ (OR, 2.56; 95%CI, 1.80-3.62) and the MVA-SLP- group (OR, 3.97; 95%CI, 2.33-6.74) were significantly higher compared with the MVA+SLP+ group.

CONCLUSION

Community-dwelling older adults who did not meet the MVPA criteria, regardless of sleep quality, had a higher prevalence of physical frailty.

Performance of the Global Diet Quality Score (GDQS) App in Predicting Nutrient Adequacy and Metabolic Risk Factors among Thai Adults

BACKGROUND

The Global Diet Quality Score (GDQS) was developed for monitoring nutrient adequacy and diet-related noncommunicable disease risk in diverse populations. A software application (GDQS app) was recently developed for the standardized collection of GDQS data. The application involves a simplified 24-h dietary recall (24HR) where foods are matched to GDQS-food groups using an onboard database, portion sizes are estimated at the food group level using cubic models, and the GDQS is computed.

OBJECTIVES

The study aimed to estimate associations between GDQS scores collected using the GDQS app and nutrient adequacy and metabolic risks.

METHODS

In this cross-sectional study of 600 Thai males and nonpregnant/nonlactating females (40-60 y), we collected 2 d of GDQS app and paper-based 24HR, food-frequency questionnaires (FFQs), anthropometry, body composition, blood pressure, and biomarkers. Associations between application scores and outcomes were estimated using multiple regression, and application performance was compared with that of metrics scored using 24HR and FFQ data: GDQS, Minimum Dietary Diversity-Women, Alternative Healthy Eating Index-2010, and Global Dietary Recommendations score.

RESULTS

In covariate-adjusted models, application scores were significantly (P < 0.05) associated with higher energy-adjusted mean micronutrient adequacy computed using 24HR (range in estimated mean adequacy between score quintiles 1 and 5: 36.3%-44.5%) and FFQ (Q1-Q5: 40.6%-44.2%), and probability of protein adequacy from 24HR (Q1-Q5: 63%-72.5%). Application scores were inversely associated with BMI kg/m2 (Q1-Q5: 26.3-24.9), body fat percentage (Q1-Q5: 31.7%-29.1%), diastolic blood pressure (Q1-Q5: 84-81 mm Hg), and a locally-developed sodium intake score (Q1-Q5: 27.5-24.0 points out of 100); positively associated with high-density lipoprotein cholesterol (Q1-Q5: 49-53 mg/dL) and 24-h urinary potassium (Q1-Q5: 1385-1646 mg); and inversely associated with high midupper arm circumference (Q5/Q1 odds ratio: 0.52) and abdominal obesity (Q5/Q1 odds ratio: 0.51). Significant associations for the application outnumbered those for metrics computed using 24HR or FFQ.

CONCLUSIONS

The GDQS app effectively assesses nutrient adequacy and metabolic risk in population surveys.

Willingness-to-pay in physical activity: how much older adults value the community-wide initiatives programs?

Background

Previous studies have shown insufficient physical activity (PA) as a significant global health concern and a major risk factor for non-communicable diseases (NCDs). Community-wide initiatives in physical activity (CWIPA) is considered as a best-buy for Community-wide initiatives in physical activity (CWIPA) is considered as a best-buy for NCDs prevention. However, assessment regarding resource allocation and cost-effectiveness of existing programs is lacking. This study investigated local residents' willingness-to-pay (WTP) for community PA programs in Southern Thailand.

Methods

The contingent valuation method (CVM) using the payment card approach was employed to elicit the WTP of 472 residents aged 45 years and over in selected provinces in which community PA programs had been implemented. Respondents were asked to indicate their WTP for the continuous offering of free CWIPA by choosing how much they were willing to pay from eight bid-value options, payable through their monthly electricity bill.

Results

The mean WTP of Thai older adults was found to be 72 baht/month ($2/month) or 868 baht/year ($25/year). This indicated the maximum amount an older person was willing to pay for any community-based PA program. More than half the sample (54.2%) chose zero as their answer, while there was a fairly large variation in other levels of WTP. The WTP was lower among older respondents and those who resided in rural areas but was higher among those with a history of participation in an organized PA program.

Conclusion

The level of WTP can be interpreted as an indicator of community satisfaction with CWIPA. That finding can be used as evidence for the government and policy makers in allocating resources and designing future CWIPA. A variety of organized PA programs should be offered to all community members to ensure inclusivity and also to provide equal access for senior citizens.

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.

Physical activity, sedentary behaviour, and sleep in the Thai population: A compositional data analysis including 135,824 participants from two national time-use surveys

PURPOSE

To determine the amounts of time spent in physical activity (PA), sedentary behaviour (SB), and sleep in the Thai population, as well as their sociodemographic correlates and changes over time.

METHODS

We analysed cross-sectional data collected in a population-representative, stratified random sample of 135,824 Thais aged 10 years and over as part of the two most recent Thai National time-use surveys (2009 and 2015). Daily activities reported by the participants were coded using the International Classification of Activities for Time-Use Statistics (ICATUS) and categorised as PA, SB, or sleep.

RESULTS

In the latest survey, participants spent on average the largest amount of time sleeping (geometric mean [g] = 9.44 h/day; 95% confidence interval [CI]: 9.42, 9.47), followed by PA (g = 8.60 h/day; 95% CI: 8.55, 8.64) and SB (g = 5.96 h/day; 95% CI: 5.93, 6.00). The time spent in PA was higher on weekdays, while the amounts of SB and sleep were higher on weekends (p < 0.05). Males, older age groups, and unemployed people spent less time in PA and more time in SB, compared with other population groups (p < 0.05). We found a relatively large increase in SB (mean difference [d] = 39.64 min/day; 95% CI: 36.18, 42.98) and decrease in PA (d = 54.33 min/day; 95% CI: -58.88, -49.30) over time. These findings were consistent across most sociodemographic groups, with the most concerning shifts from active to sedentary lifestyle found among people with a higher education degree and on weekends.

CONCLUSIONS

Our findings revealed a shift to a more sedentary lifestyle in the Thai population. Public health interventions should focus on improving time use among males, older age groups, and unemployed people, while preventing the rapid decrease in PA and increase in SB among those with a higher education degree and on weekends.

Refining index to measure physical activity inequality: which group of the population is the most vulnerable?

BACKGROUND

The existing body of research mostly discusses inequality in physical activity (PA) based on the difference in the level of moderate-to-vigorous physical activity (MVPA). Evidence is lacking on the quantified inequality measures (e.g., how big the inequality is, and the distribution) in order to identify the most vulnerable groups of a population. This study measured PA inequality among Thai adults by using three parameters to construct an inequality index: (1) Proportion of the population with sufficient MVPA; (2) Cumulative minutes of MVPA; and (3) The Gini coefficient.

METHODS

This study employed three rounds of data from Thailand's Surveillance on Physical Activity (SPA) 2019-2021. In each round, over 6,000 individuals age 18-64 years were selected as nationally-representative samples, and were included in the analysis. PA inequality was constructed by using three parameters, with a combination of the three as the final measure, to identify the sub-groups of the Thai adults who are most vulnerable: groups with the least MVPA, highest insufficiency, and highest inequality index (Gini).

RESULTS

Covid-19 containment measures have widened the gap in PA inequality, as shown by a declining proportion of the population meeting the recommended guidelines, from 74.3% in 2019 to 56.7% in 2020 and 65.5% in 2021. PA inequality existed in all sub-populations. However, by combining three parameters, the most vulnerable groups during the Covid-19 epidemic were identified as follows: (1) Those with no income; (2) The unemployed; (3) Those who have no access to PA facilities; (4) Older adults aged 60 + years; and (5) Those earning < 3,500 baht per month. Further, residents of Bangkok, young adults aged 18-24, individuals who attained primary level education or less, those who had no exposure to a PA awareness campaign and those who have a debilitating chronic disease also had elevated risk of PA insufficiency.

CONCLUSION

A concerning level of PA inequality existed in all sub-populations. The use of combined indicators in measuring PA inequality should aid in determining the most vulnerable groups of the population with a refined procedure. This method can be applied in many settings since the baseline data used to measure inequality (i.e., percent sufficient and cumulative minutes of MVPA) are widely available.