PLoS ONE (Jan 2015)

Physical Activity in Vietnam: Estimates and Measurement Issues.

  • Tan Van Bui,
  • Christopher Leigh Blizzard,
  • Khue Ngoc Luong,
  • Ngoc Le Van Truong,
  • Bao Quoc Tran,
  • Petr Otahal,
  • Velandai Srikanth,
  • Mark Raymond Nelson,
  • Thuy Bich Au,
  • Son Thai Ha,
  • Hai Ngoc Phung,
  • Mai Hoang Tran,
  • Michele Callisaya,
  • Seana Gall

DOI
https://doi.org/10.1371/journal.pone.0140941
Journal volume & issue
Vol. 10, no. 10
p. e0140941

Abstract

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Our aims were to provide the first national estimates of physical activity (PA) for Vietnam, and to investigate issues affecting their accuracy.Measurements were made using the Global Physical Activity Questionnaire (GPAQ) on a nationally-representative sample of 14706 participants (46.5% males, response 64.1%) aged 25-64 years selected by multi-stage stratified cluster sampling.Approximately 20% of Vietnamese people had no measureable PA during a typical week, but 72.9% (men) and 69.1% (women) met WHO recommendations for PA by adults for their age. On average, 52.0 (men) and 28.0 (women) Metabolic Equivalent Task (MET)-hours/week (largely from work activities) were reported. Work and total PA were higher in rural areas and varied by season. Less than 2% of respondents provided incomplete information, but an additional one-in-six provided unrealistically high values of PA. Those responsible for reporting errors included persons from rural areas and all those with unstable work patterns. Box-Cox transformation (with an appropriate constant added) was the most successful method of reducing the influence of large values, but energy-scaled values were most strongly associated with pathophysiological outcomes.Around seven-in-ten Vietnamese people aged 25-64 years met WHO recommendations for total PA, which was mainly from work activities and higher in rural areas. Nearly all respondents were able to report their activity using the GPAQ, but with some exaggerated values and seasonal variation in reporting. Data transformation provided plausible summary values, but energy-scaling fared best in association analyses.