[The usefulness of descriptive statistics in the interpretation of data on occupational physical activity of Poles]

Med Pr. 2014;65(6):743-53.
[Article in Polish]

Abstract

Background: The aim of this paper is to assess whether basic descriptive statistics is sufficient to interpret the data on physical activity of Poles within occupational domain of life.

Material and methods: lhe study group consisted of 964 randomly selected Polish working professionals. The long version of the International Physical Activity Questionnaire (IPAQ) was used. Descriptive statistics included characteristics of variables using: mean (M), median (Me), maximal and minimal values (max-min.), standard deviation (SD) and percentile values. Statistical inference was based on the comparison of variables with the significance level of 0.05 (Kruskal-Wallis and Pearson's Chi2 tests).

Results: Occupational physical activity (OPA) was declared by 46.4% of respondents (vigorous - 23.5%, moderate - 30.2%, walking - 39.5%). the total OPA amounted to 2751.1 MET-min/week (Metabolic Equivalent of Task) with very high standard deviation (SD) = 5302.8 and max = 35 511 MET-min/week. It concerned different types of activities. Approximately 10% (90th percentile) overstated the average. However, there was no significant difference depended on the character of the profession, or the type of activity. The average time of sitting was 256 min/day. As many as 39% of the respondents met the World Health Organization standards only due to OPA (42.5% of white-collar workers, 38% of administrative and technical employees and only 37.9% of physical workers).

Conclusions: In the data analysis it is necessary to define quantiles to provide a fuller picture of the distributions of OPA in MET-min/week. It is also crucial to update the guidelines for data processing and analysis of long version of IPAQ. It seems that 16 h of activity/day is not a sufficient criterion for excluding the results from further analysis.

Publication types

  • English Abstract

MeSH terms

  • Adult
  • Energy Metabolism* / physiology
  • Female
  • Health Status
  • Humans
  • Male
  • Middle Aged
  • Motor Activity* / physiology
  • Occupational Health / statistics & numerical data*
  • Occupations / statistics & numerical data*
  • Poland / epidemiology
  • Surveys and Questionnaires
  • Task Performance and Analysis*
  • Walking / physiology
  • Young Adult